Real-time
Two-way sync
Changes in Elasticsearch or SingleStore instantly reflect in both systems. No stale data, no manual imports.
Database
Elasticsearch to SingleStore integration — real-time, two-way sync
Keep Elasticsearch and SingleStore 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
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Elasticsearch and SingleStore
Keep Elasticsearch and SingleStore synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Elasticsearch and SingleStore continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- Mirror support tickets into an index used for full-text search and agent-assist tooling.
- Feed enriched customer records into an index used for vector or hybrid search in AI applications.
- Mirror CRM and SaaS objects into SingleStore tables to serve low-latency operational dashboards.
- Sync results of real-time analytical queries back into business tools where teams act on them.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both Elasticsearch and SingleStore, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
What you can sync between Elasticsearch and SingleStore
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.
| Elasticsearch objects | SingleStore objects | |
|---|---|---|
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | Databases The connection target containing the tables a sync addresses. | |
| Index mappings Field type definitions that determine how synced fields are indexed and queried. | Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. | |
| Aliases Stable read/write names that let a sync cut over between index versions without downtime. | Views Read-only projections used as curated sync sources. | |
| Data streams Append-only targets for time-series or event data pushed from source systems. | Reference Tables Small tables replicated to every node, often used for dimension data in syncs. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Stored Procedures Existing logic sometimes invoked on write paths. |
What ships with Elasticsearch ⇄ SingleStore
Connect Elasticsearch and SingleStore for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–SingleStore connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Elasticsearch or SingleStore 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 Elasticsearch or SingleStore record.
Observability
Monitoring
Track your Elasticsearch ⇄ SingleStore sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Elasticsearch and SingleStore.
How the Elasticsearch and SingleStore connectors work
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
SingleStore
- Integration surface
- SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
- Authentication
- Database credentials
- Change detection
- Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by workspace or cluster size
How it works
How to connect Elasticsearch to SingleStore — 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 Elasticsearch and SingleStore with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Elasticsearch
connected
SingleStore
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Elasticsearch and SingleStore 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 · Elasticsearch ⇄ SingleStoreCustomers 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.
Elasticsearch SingleStoreCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Elasticsearch and SingleStore integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Elasticsearch and SingleStore: authenticate both systems, choose the objects to sync (such as Elasticsearch's Documents and Index mappings), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Elasticsearch side: Data streams, Ingest pipelines, Index templates, Indices, plus custom fields where Elasticsearch exposes them. On the SingleStore side: Databases, Tables (rowstore and columnstore), Views, Reference Tables. 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 Elasticsearch and SingleStore: Regional or environment copies; Cross-engine sync; Migration with zero-downtime cutover. Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
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Elasticsearch: REST API (JSON over HTTP). Authentication: API keys or basic authentication; Elastic Cloud also issues service account tokens. SingleStore: SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST. Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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Elasticsearch: Optimistic concurrency uses _seq_no and _primary_term instead of row locks, which matters when two writers touch the same document. SingleStore: SingleStore is compatible with the MySQL wire protocol, so standard MySQL drivers and clients connect without modification. Stacksync's field mapping accounts for these differences between Elasticsearch and SingleStore 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 Elasticsearch and SingleStore.
Popular · 8 of 386
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Elasticsearch ⇄ InfluxDB -
Elasticsearch ⇄ InterSystems IRIS -
Elasticsearch ⇄ MarkLogic -
Elasticsearch ⇄ Neo4j -
SingleStore ⇄ Airtable -
SingleStore ⇄ AWS Aurora MySQL - SingleStore ⇄ AWS Aurora PostgreSQL
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SingleStore ⇄ MongoDB
No integrations match .
