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Data warehouse ⇄ Database

Dremio to Elasticsearch integration — real-time, two-way sync

Keep Dremio and Elasticsearch in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Dremio and Elasticsearch

Connect Elasticsearch and Dremio with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Elasticsearch's rows in Dremio, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Elasticsearch where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Elasticsearch sync into Dremio in real time, and result tables in Dremio sync back into Elasticsearch, with schema and type mapping between the two systems handled for you.

Common use cases

  • Publish operational database tables into Iceberg via Dremio so the lakehouse reflects current application state.
  • Consolidate data from multiple lake sources through one Dremio semantic layer into a single warehouse target.
  • Feed enriched customer records into an index used for vector or hybrid search in AI applications.
  • Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.

Operational data in the warehouse, minus the pipeline

Rows from Elasticsearch land in Dremio as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Dremio sync into Elasticsearch, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

What you can sync between Dremio and Elasticsearch

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Dremio objects Elasticsearch objects
Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. Indices Target containers for synced records; each holds a table-like collection of JSON documents.
Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. Documents The unit of sync; JSON records created, updated, and deleted by _id.
Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. Index mappings Field type definitions that determine how synced fields are indexed and queried.
Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. Aliases Stable read/write names that let a sync cut over between index versions without downtime.
Spaces and folders Namespaces that organize virtual datasets and govern access. Data streams Append-only targets for time-series or event data pushed from source systems.
Reflections Materialized accelerations that make repeated extraction queries cheaper. Ingest pipelines Server-side transforms applied to documents as a sync writes them.
What ships with Dremio ⇄ Elasticsearch

Connect Dremio and Elasticsearch for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–Elasticsearch connection.

Real-time

Two-way sync

Changes in Dremio or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Dremio or Elasticsearch data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Dremio or Elasticsearch record.

Observability

Monitoring

Track your Dremio ⇄ Elasticsearch sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Dremio and Elasticsearch.

How the Dremio and Elasticsearch connectors work

Dremio

Integration surface
Arrow Flight SQL, JDBC/ODBC, and a REST API
Authentication
Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
Change detection
Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
Capabilities
read · write
Rate limits
Bounded by engine capacity and workload management rather than API rate limits

Elasticsearch

Integration surface
REST API (JSON over HTTP)
Authentication
API keys or basic authentication; Elastic Cloud also issues service account tokens
Change detection
Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
Capabilities
read · write
Rate limits
No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity
How it works

How to connect Dremio to Elasticsearch — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Dremio and Elasticsearch with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Dremio connected
    Elasticsearch connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Dremio and Elasticsearch objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Dremio ⇄ Elasticsearch
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Dremio Elasticsearch
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Dremio and Elasticsearch integration FAQ

SECURITY

Security teams love Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Dremio and Elasticsearch.

Popular · 8 of 386
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