Load Elasticsearch data to Amazon Redshift in minutes.
Load your Elasticsearch data to your data warehouse to run custom SQL queries on your analytic events and to generate custom reports and dashboards. Combine your Elasticsearch data with other data sources to make it even more valuable.
Load data from any source.Alooma natively supports dozens of the most popular data sources.
Loading Elasticsearch Data to Redshift
Replicate Whole Index Snapshots to RedshiftSuitable for Periodically copying elasticsearch to Redshift. What is it REST based connector that periodically runs a match all query, to dump a whole index and match it to BigQuery. How it works
- Specify the name of an INDEX
- Specify the replication frequency
- Alooma’s connector will dump the whole index and load it to BigQuery
Incrementally Replicate an Elasticsearch QuerySuitable for Continuous replication of query results. What is it Elasticsearch connector that continuously queries for changes and replicates them to Redshift. How it works
- Select index to query
- Add a query
- Incrementally query the index
Elasticsearch to Redshift - Should you do it yourself or use a third party solution?
Elasticsearch poses two difficulties for the replicating connector. The first is the lack of a native mechanism for ordering documents (aka items) within an index. This makes incremental replication dependent on a manually enforced document field which contains the last update time.
The second difficulty is the way schemas (aka mappings) are managed in Elasticsearch. Since it is completely different from relational schemas, it makes the translation to tables a bit more difficult. To avoid this, you can use the Alooma Mapper to update schemas automatically.
Calculate how much it would cost to build your own data pipeline in-house here.
Export your Elasticsearch data along with all of
your other data sources to Amazon Redshift.
Extract, transform and load (ETL) your Elasticsearch data to your data warehouse using Alooma's stream-based data pipeline as a service to run custom SQL queries on your analytic events and to generate custom reports and dashboards. Combine your Elasticsearch data with other data sources to make it even more valuable.