Connecting Relational Databases to Elasticsearch®
Use Elasticsearch to add visualization and full text search to your SQL data.
It’s not uncommon for users of relational databases like MySQL, PostgreSQL, MS SQL Server, or Oracle to want to replicate data into Elasticsearch to boost search capabilities or for data analytics purposes. By adding Elasticsearch to your data portfolio, you gain the ability to perform fast ad-hoc analytics, full-featured text search, and easy-to-use visualization all via an open source platform. This can help you reduce the load on our mission critical relational data while enabling you to learn more from your data—faster.
We are often asked the question of how to best use Elasticsearch in conjunction with these other well-established relational databases. There are some excellent tools available to provide this desired replication of data, but they can be hard to find on your own. Take advantage of our expertise by downloading this whitepaper to learn where to begin with making this data connection.
In this whitepaper, we will cover everything you need to know to work PostgreSQL into Elasticsearch, to work MySQL into Elasticsearch, or most relational databases into Elasticsearch with a specific example. However, the concepts are flexible enough that you can apply them with other technologies. Submit your information to download a copy today.
Elasticsearch is a fully-featured open source search engine and document store that is surrounded by a rich ecosystem of tools, clients and backed by a passionate community. By adopting Elasticsearch, you’re opening the door to a rapidly growing technology and community that provides Enterprise-level features and stability in an open source model. As you become more familiar with what Elasticsearch can do for you and your data, you will continue to find applications where Elasticsearch can improve your processes, performance, and capabilities. All of this is available without requiring you to move off of the relational databases you know and trust.