datazip-inc

datazip-inc/olake

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

1.4K stars 241 forks 1.4K watchers Go Apache License 2.0

apache-iceberg cdc change-data-capture data-pipeline database elt hacktoberfest kafka lakehouse parquet replication s3

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54 Open Issues Need Help Last updated: Aug 2, 2026

Open Issues Need Help

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feat: Add Unit Tests for state.go about 22 hours ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Integration Tests for Discover & Merging (Selection, Unselection) about 1 month ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Feat: Auto select a cursor value incase of default Incremental sync mode about 2 months ago

good first issue beginner

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add Unit Tests for stream.go about 2 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

issue(postgres): check connection in postgres not check for database of replication slot about 2 months ago

good first issue beginner SWoC26

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

issue(postgres): check if tables selected in streams.json are subscribed in publication about 2 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Add consistent timezone detection for CDC of other drivers as well. 4 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Make this function more efficient by using a single query to get all the rowids in the table using one query 4 months ago

good first issue beginner

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

fix: fasten the integration test (current time ~17 mins) 5 months ago

good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: switch mysql cdc state tracking from binlog positions to gtid sets 5 months ago

help wanted question good second issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

MSSQL CDC: robust schema-evolution handling across capture instance create/drop 5 months ago

help wanted in-roadmap good second issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add Unit Tests for stream_configured.go 6 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add Unit Tests for reformat.go 6 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add Unit Tests for datatype.go 6 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

fix(MariaDB): GTID event structure with microsecond precision for _cdc_timestamp column 6 months ago

good first issue todo :spiral_notepad: beginner SWoC26

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Integration Tests for Denormalization 7 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Add Elasticsearch / OpenSearch as a Source Connector 7 months ago

help wanted good second issue feature-request SWoC26

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: schema type changes handling in parquet writer 7 months ago

help wanted

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

fix: take val as any type in mongodb 7 months ago

improvement good first issue todo :spiral_notepad: hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

improvement: use batch writing feature of parquet writer 7 months ago

improvement good first issue beginner SWoC26

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

improvement: after normalization, record of type rawRecord need to be changed 7 months ago

improvement good first issue beginner SWoC26

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add Unit Tests for compare.go 7 months ago

good first issue beginner SWoC26

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

improvement: enabling stats on resumed sync 7 months ago

good first issue help wanted hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Integration Test for Kafka Source 7 months ago

good first issue todo :spiral_notepad:

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add SSL protocol support and external certificate handling for Kafka dialer 8 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

fix: handle special characters in column name in filter 9 months ago

good first issue todo :spiral_notepad:

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: SSH support for mongodb and oracle drivers 9 months ago

good first issue feature-request hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

[Improvement] Revamp config.json 9 months ago

improvement good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Fix `filterMongoObject` is not recursive, causing crashes on nested `DateTime` fields 10 months ago

bug improvement good first issue help wanted hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Add implementation of AddRecordsToSync function in Oracle to estimate remaining sync time 10 months ago

good first issue todo :spiral_notepad: hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

BigInt value difference with postgres in Parquet Writer 10 months ago

bug good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: source ClickHouse 10 months ago

help wanted good second issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: source S3 10 months ago

help wanted in-roadmap advanced level issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

task: Use documentKey Instead of _id for Change Event Keys in Sharded MongoDB 10 months ago

improvement help wanted good second issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

bug: MongoDB timestamps with year 0 cause JSON marshaling error 10 months ago

bug good first issue help wanted hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

improvement: use context while querying (sql/sqlx) 10 months ago

good first issue todo :spiral_notepad: hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: add JDBC URL params and SSL config support to MySQL connector 10 months ago

good first issue todo :spiral_notepad: hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

chore: integration test for schema evolution 10 months ago

improvement good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: uuid as split column in postgres 10 months ago

good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

[Feat] HeartBeating similar to Debezium 11 months ago

help wanted advanced level issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

improvement: Parallel process postgres wal logs changes 11 months ago

good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Clear Destination And Sync 11 months ago

good first issue hacktoberfest

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Dead Letter Queue (DLQ) feature 11 months ago

improvement help wanted in-roadmap advanced level issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: source FTP/FTPS/SFTP 11 months ago

help wanted good second issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: source SAP HANA (On premise/ Cloud) 11 months ago

help wanted good second issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: source Trino 11 months ago

improvement help wanted good second issue feature-request

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

chore: check if writer instance need to create again on retry 11 months ago

help wanted question

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: iceberg rust writer 11 months ago

help wanted advanced level issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

[Feat] sync only selected columns from catalog.json 11 months ago

documentation help wanted

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

[Improvement] Iceberg-writer should accommodate parsable schema type changes 11 months ago

improvement help wanted

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Avoid Sync Failure in MySQL when Table has 0 Records 11 months ago

bug good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

task: normalisation true by default for all relational sources 11 months ago

good first issue

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

feat: Integration test for Oracle 11 months ago

good first issue todo :spiral_notepad:

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3

Integration tests for MongoDB 11 months ago

good first issue todo :spiral_notepad:

datazip-inc/olake

1.4K

OLake - Fastest Databases, Kafka & S3 Replication to Apache Iceberg with Table optimization (Called OLake Fusion). ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supported sources : Postgres, MongoDB, MySQL, Oracle, MSSql, DB2, Kafka, S3.

Go

#apache-iceberg#cdc#change-data-capture#data-pipeline#database#elt#hacktoberfest#kafka#lakehouse#parquet#replication#s3