Real-time
Two-way sync
Changes in Apache Doris or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Apache Doris to Elasticsearch integration — real-time, two-way sync
Keep Apache Doris 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 Apache Doris and Elasticsearch
Connect Elasticsearch and Apache Doris 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 Apache Doris, 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 Apache Doris in real time, and result tables in Apache Doris sync back into Elasticsearch, with schema and type mapping between the two systems handled for you.
Common use cases
- Read aggregates from Doris and sync them into business tools like CRMs or spreadsheets.
- Consolidate event and transactional data from multiple sources into one real-time OLAP layer.
- 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.
Serve warehouse results at database speed
Aggregates or model outputs computed in Apache Doris 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.
Offload heavy reads
Point analytical queries at the synced copy in Apache Doris and keep Elasticsearch focused on its operational workload.
What you can sync between Apache Doris 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.
| Apache Doris objects | Elasticsearch objects | |
|---|---|---|
| Partitions Range or list partitions that bound incremental loads. | Index mappings Field type definitions that determine how synced fields are indexed and queried. | |
| Materialized Views Precomputed views readable for downstream syncs and BI. | Aliases Stable read/write names that let a sync cut over between index versions without downtime. | |
| Users and Roles Principals used to grant the sync connection scoped access. | Data streams Append-only targets for time-series or event data pushed from source systems. | |
| Databases Logical containers that scope connections and grants. | Ingest pipelines Server-side transforms applied to documents as a sync writes them. | |
| Tables Columnar tables in one of Doris's table models, used as sync destinations. | Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | |
| Unique Key Tables Tables supporting primary-key upserts, the natural target for row-level syncs. | Indices Target containers for synced records; each holds a table-like collection of JSON documents. |
What ships with Apache Doris ⇄ Elasticsearch
Connect Apache Doris and Elasticsearch for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Doris–Elasticsearch connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Doris 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 Apache Doris or Elasticsearch record.
Observability
Monitoring
Track your Apache Doris ⇄ Elasticsearch sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Apache Doris and Elasticsearch.
How the Apache Doris and Elasticsearch connectors work
Apache Doris
- Integration surface
- MySQL wire protocol for SQL access; HTTP APIs (such as Stream Load) for bulk ingestion
- Authentication
- Database credentials
- Change detection
- Polling on partition or timestamp columns for reads; ingestion into Doris is push-based via load jobs
- Capabilities
- read · write
- Rate limits
- No API quotas; load throughput depends on cluster resources and load-job configuration
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 Apache Doris 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.
- 01
Connect your apps
Authenticate Apache Doris 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.
Apache Doris
connected
Elasticsearch
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Doris 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.
objects · Apache Doris ⇄ ElasticsearchCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Apache Doris ElasticsearchCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Doris and Elasticsearch integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Apache Doris and Elasticsearch: authenticate both systems, choose the objects to sync (such as Apache Doris's Partitions and Materialized Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Apache Doris side: Aggregate Key Tables, Partitions, Materialized Views, Users and Roles, plus custom fields where Apache Doris exposes them. On the Elasticsearch side: Ingest pipelines, Index templates, Indices, Documents. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Apache Doris and Elasticsearch: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Apache Doris sync into Elasticsearch, where whatever reads from that database gets them without querying the warehouse.
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Apache Doris: MySQL wire protocol for SQL access; HTTP APIs (such as Stream Load) for bulk ingestion. Authentication: Database credentials. Elasticsearch: REST API (JSON over HTTP). Authentication: API keys or basic authentication; Elastic Cloud also issues service account tokens. Stacksync manages authentication, retries, and rate limits on both sides.
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Apache Doris: Bulk ingestion is HTTP-based through mechanisms like Stream Load, which is separate from the SQL query path. Elasticsearch: Optimistic concurrency uses _seq_no and _primary_term instead of row locks, which matters when two writers touch the same document. Stacksync's field mapping accounts for these differences between Apache Doris and Elasticsearch without custom code.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Doris and Elasticsearch.
Popular · 8 of 386
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Apache Doris ⇄ Azure SQL Database -
Apache Doris ⇄ Citus -
Apache Doris ⇄ Couchbase -
Apache Doris ⇄ DuckDB -
Elasticsearch ⇄ Firebolt -
Elasticsearch ⇄ Google Cloud Platform -
Elasticsearch ⇄ Greenplum -
Elasticsearch ⇄ IBM Netezza
No integrations match .
