Ensures robust real-time data replication to AWS S3, supporting RDBMS/NoSQL databases. Version 1.3 enables efficient JSON-format storage in S3 buckets, ideal for data lakes/cold storage. Features Docker distribution, major cloud provider compatibility, two-way sync, and simple setup. Optimizes cloud transition with immediate data availability.

Gluesync for AWS S3

Real-time data replication to AWS S3 made simple for analytics, data lakes & cold storage

Make Amazon S3 data actionable for AI, ML, data lakes and more

Gluesync provides a robust, cloud-native solution for real-time RDBMS and NoSQL data replication directly into AWS S3 buckets. This integration facilitates a variety of use cases, including data lakes and cold object storage, ensuring that your transition to modern storage solutions is efficient and secure

A universe of possibilities

What can you achieve by replicating data within a large object store?

You can redefine how you think about data costs by implementing a real-time data pipeline from your business systems, either running over an RDBMS or a blazing-fast NoSQL towards an AWS S3 bucket. Large object storages, like AWS S3, offer an effective solution for cold data storage with easy-definable storage policies to cut down your costs per gigabyte. Additionally, you gain power over a single source of truth, which soon becomes a Data lake suitable for massive query and analytics use cases

Feed your bucket with real-time data

Today’s enterprises have all the rights to enter the right now economy, so why should yours have to wait?

With Gluesync’s real-time CDC (change data capture) engine your AWS S3 bucket can be linked with any major datasource and fed with only incoming incremental changes so your decision-making and AI tools can be immediately actionable

Data modeling

Customizable data models or just skip deletions

Data lakes, Big data, or data warehouses may require tailored approaches, which is better if no code is required

Gluesync comes to help in designing your new data lake by giving you powerful tools like its advanced data modeling engine and the ability to skip record deletions with a simple flag. Querying data that has been modeled and transformed before storing it is a crucial requirement when dealing with large data sets, saving you precious time-to-insights and helping drive down costs

Replicate with no boundaries

From major RDBMSes
to AWS S3

Effortlessly replicate your data from major relational databases to Amazon S3. GlueSync supports a wide range of RDBMS such as Microsoft SQL Server, Oracle, IBM Db2, MySQL, and more, offering snapshot and CDC replication. Your data is stored in JSON format, fully compatible with AWS S3, and is readily accessible for analytics or other applications

From NoSQL
to AWS S3

With GlueSync, move your NoSQL data into AWS S3 it’s easy: no need to code or re-architect your current solution. Gluesync supports object storage, transforming your data into a flexible JSON format and leveraging AWS S3’s SDK for seamless storage operations and security. Customize your data modeling and ensure optimal data organization within your S3 buckets for efficient future-proof data retrieval

What makes Gluesync unique​

Data modeling with nested objects support

Gluesync offers on-the-fly data modeling with support for ANSI SQL queries to describe the data model for the JSON document structure in NoSQL you'd like to get but it is not limited to that: through our Advanced data modeling feature you can nest incoming RDBMS objects into your JSON document with up to 2 level of deep

Transactions log-based CDC plus a blazingly-fast initial load​

  • Take data out of any major RDBMS or NoSQL at incredible speeds
  • Replicate data changes incrementally avoiding risky data refreshes or heavy data imports
  • Every action counts: by reading your datasource's transaction logs Gluesync replays every each action happened to your data whether is an INSERT, UPDATE or a DELETE
  • Don't miss a single bit: your transactions are securely replayed to the target datastore only when our 2-phases commit implementation acknowledge the engine that every bit has been securely persisted
  • Reduced footprint: by managing and implementing change data capture via native datasource APIs we're always up-to-date with latest vendor updates and optimizations

Enterprise features

  • Built-in alerting system
  • Monitoring via Prometheus and REST API endpoints
  • Logging: fully user-customizable for advanced traceability
  • Designed for the containers era: natively supporting Kubernetes & Openshift

Access plenty of connectors, constantly evolving

Here is just a sample of the ever-increasing number of relational and non-relational databases Gluesync supports as replication sources: Oracle, Microsoft SQL Server, IBM Db2, MySQL, PostgreSQL, MariaDB, SAP ASE, Couchbase, DynamoDB, MongoDB and HBase. Check out the Gluesync documentation for a full matrix of all supported databases and features

Begin your data journey with AWS S3 and Gluesync today

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