Source connector

Elasticsearch connector

Elasticsearch integration for databases, warehouses and BI tools

Search and analytics engine over document indices. Datrise captures Elasticsearch entities such as indices, documents, mappings, fields, search queries and aliases, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Elasticsearch REST API (Search, Scroll, Point in Time) authenticates with API key, HTTP Basic.

Of the 6 objects, 6 sync as upserts keyed on the primary key and 0 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `elasticsearch_indices`) with a schema derived from the Elasticsearch API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Elasticsearch pipeline page, and join the waitlist to get the Elasticsearch connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Elasticsearch data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
indices	elasticsearch_indices	Upsert by primary key, incremental on updated-at
documents	elasticsearch_documents	Upsert by primary key, incremental on updated-at
mappings	elasticsearch_mappings	Upsert by primary key, incremental on updated-at
fields	elasticsearch_fields	Upsert by primary key, incremental on updated-at
search queries	elasticsearch_search_queries	Upsert by primary key, incremental on updated-at
aliases	elasticsearch_aliases	Upsert by primary key, incremental on updated-at

Elasticsearch API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Elasticsearch REST API (Search, Scroll, Point in Time)
Authentication	API key, HTTP Basic — Self-managed and Elastic Cloud clusters accept HTTP Basic auth or an API key (`Authorization: ApiKey <encoded>`); Elastic Cloud also supports bearer tokens for its own console/API.
Pagination	cursor — `from`/`size` pagination is capped by `index.max_result_window` (default 10,000); deep pagination uses either the Scroll API (`scroll` context timeout, e.g. `1m`, returning a `_scroll_id`) or the recommended Point-in-Time (`pit.id` + `keep_alive`) combined with `search_after` and a sort tiebreaker.
Rate limit	Not published
Incremental cursor	Not published
Webhooks	No
Bulk export	No
Deletes detectable	No

Official API reference

What bites when replicating Elasticsearch

`from`+`size` pagination throws `illegal_argument_exception` ("Result window is too large") once `from + size` exceeds `index.max_result_window`, which defaults to 10,000 documents per index — a connector must switch to `search_after`/PIT before that ceiling, not after hitting the error.
The Scroll API's `scroll` context timeout (e.g. `1m`) is a hard TTL on the search snapshot; a slow downstream write that stalls longer than the timeout invalidates the `_scroll_id` and forces the whole scroll to restart from page one.
Deleted documents are only preserved internally as Lucene tombstones governed by `index.gc_deletes` (default 60 seconds) for concurrency control, not as a queryable deletes feed, so there is no API-level way to detect deletions after that window without an external changes log (e.g. CDC on the write path).
`search_after` requires a sort that resolves to a unique total order (Elasticsearch appends an implicit `_shard_doc` tiebreaker under Point in Time); sorting on a non-unique field alone can silently skip or duplicate documents across pages.

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Popular destinations for Elasticsearch

Choose a destination below to open the ready pipeline page.

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Elasticsearch connector FAQ

What Elasticsearch data does the connector extract?: 6 objects: indices, documents, mappings, fields, search queries and aliases. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the Elasticsearch integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Elasticsearch data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Elasticsearch → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Elasticsearch pipeline with guided onboarding

Join the waitlist to get priority access for Elasticsearch integrations with guided setup, schema-aware mapping, and production-grade incremental sync.