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DynamoDB

DynamoDB is a serverless, NoSQL database service from Amazon that enables you to develop modern applications at any scale. DynamoDB is scalable, fast and flexible. Streamkap can connect to via DynamoDB streams for real-time change data capture. For historical data, Streamkap uses DynamoDB’s S3 export feature for cost-efficient backfilling of data.

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DynamoDB real-time ETL using change data capture (CDC)

  • Uses Change Data Capture (CDC) to read data from DynamoDB Streams
  • Snapshot/Backfill historical data via S3 exports and point-in-time recovery (PITR)
  • Can include/exclude table/columns
  • Schema evolution support for supported destinations
  • Setup DynamoDB change data capture in minutes
  • Sub-second latency

‍

Marcin Migda

Staff Data Engineer

"Streamkap was 4x faster and had 3x lower total cost of ownership than our previous solution"

Why Streamkap?

Reliable

Serverless platform providing enterprise reliability and scale.

Affordable

Only pay for GB into Streamkap.

Longterm

Retain data for as long as you need.

Flexible

Read once, write to many destinations.

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DynamoDB

DynamoDB is a serverless, NoSQL database service from Amazon that enables you to develop modern applications at any scale. DynamoDB is scalable, fast and flexible. Streamkap can connect to via DynamoDB streams for real-time change data capture. For historical data, Streamkap uses DynamoDB’s S3 export feature for cost-efficient backfilling of data.

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Db2

Db2 is a database product from IBM. It is a Relational Database Management System (RDBMS). Db2 is designed to store, analyze and retrieve the data efficiently. Db2 product is extended with the support of Object-Oriented features and non-relational structures with XML.

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Vitess

Vitess is an open source system for database clustering that allows for the horizontal scaling of MySQL databases. Vitess was originally developed at YouTube and is used by some of the largest websites in the world. Vitess combines the features of MySQL with the scalability of a NoSQL database, and uses sharding to separate large databases into smaller, more manageable parts.

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