Two-way sync
Changes in Datadog or VoltDB instantly reflect in both systems. No stale data, no manual imports.
Keep Datadog and VoltDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
VoltDB is where your application's durable data lives; Datadog is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.
Stacksync syncs Export Targets and Topics, Partitioned Tables, Replicated Tables, Stored Procedures in VoltDB with Service Level Objectives, Hosts, Monitors, Logs in Datadog field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.
Directory and identity records in Datadog stay matched to the users or owners table in VoltDB, so provisioning and de-provisioning flow from one source.
A new or changed row in VoltDB creates or updates the matching record in Datadog, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.
Records and events from Datadog arrive in VoltDB as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
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.
| Datadog objects | VoltDB objects | How this pairing syncs | |
|---|---|---|---|
| Dashboards Dashboard definitions and widgets via the v1 Dashboards API with full CRUD; exported for backup and audit, or created and updated programmatically from a source of truth. | Replicated Tables Small reference tables copied to every partition, a common landing spot for synced lookup data. | Dashboards is specific to Datadog and Replicated Tables to VoltDB — each maps to any object or custom field on the other side. | |
| Metrics Time-series metrics queried in aggregate windows through the query API and submitted via POST /api/v1/series; individual raw points cannot be extracted beyond retention. | Stored Procedures Precompiled transactional units that serve as the primary write interface. | Metrics is specific to Datadog and Stored Procedures to VoltDB — each maps to any object or custom field on the other side. | |
| Incidents Incident records from the v2 Incidents API with full CRUD, including status and timeline fields; landed in a database for MTTR reporting or created and updated from an external incident workflow. | Materialized Views Synchronously maintained aggregates over tables, useful as pre-computed read sources. | Incidents is specific to Datadog and Materialized Views to VoltDB — each maps to any object or custom field on the other side. | |
| Service Level Objectives SLO definitions and status history via the v1 SLO API with full CRUD; read out for reliability and error-budget reporting, or provisioned and updated from a reliability config. | Streams Insert-only constructs that feed the export subsystem with committed rows. | Service Level Objectives is specific to Datadog and Streams to VoltDB — each maps to any object or custom field on the other side. | |
| Hosts Infrastructure host inventory with tags and metadata from the v1 host list API; loaded into a CMDB or warehouse for asset tracking, and hosts can be muted or unmuted via the API. | Export Targets and Topics Connectors that push committed data to external systems such as Kafka or JDBC sinks. | Hosts is specific to Datadog and Export Targets and Topics to VoltDB — each maps to any object or custom field on the other side. | |
| Monitors Alert definitions with query, thresholds, and current state via the v1 Monitors API, which supports full create, update, and delete; Stacksync reads alert state into a warehouse or provisions and updates monitors from a config source. | Partitioned Tables Tables sharded across partitions by a partitioning column; the primary transactional store and sync target. | Monitors is specific to Datadog and Partitioned Tables to VoltDB — each maps to any object or custom field on the other side. |
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
DetectionDatadog notifies Stacksync of record changes through webhook events. Polling with time-windowed search queries on Logs and Events (timestamp cursor).
DeliveryEach detected change is applied to VoltDB as a row-level write, with types converted between the two schemas.
DetectionStacksync polls VoltDB for changes on an incremental schedule, reading only records changed since the previous pass. Export streams and topics push committed changes to configured targets.
DeliveryEach detected change is written to Datadog through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Datadog–VoltDB connection.
Changes in Datadog or VoltDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Datadog or VoltDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Datadog or VoltDB record.
Track your Datadog ⇄ VoltDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Datadog and VoltDB.
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.
Authenticate Datadog and VoltDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Datadog and VoltDB 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Datadog and VoltDB: authenticate both systems, choose the objects to sync (such as Datadog's Dashboards and Metrics), map fields visually, and changes propagate both ways in milliseconds — no code required.
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.
Common patterns for Datadog and VoltDB: Where Datadog manages users or groups: keep identity aligned; Turn rows into the records your tools track; Land tool activity as queryable rows. Directory and identity records in Datadog stay matched to the users or owners table in VoltDB, so provisioning and de-provisioning flow from one source.
Datadog: REST API (v1 and v2). Authentication: API key (DD-API-KEY) plus an Application key (DD-APPLICATION-KEY) sent as request headers; application keys are tied to the creating user and inherit that user's permissions and authorization scopes. VoltDB: SQL over JDBC plus native client libraries and an HTTP/JSON interface. Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
VoltDB: Transactions execute as stored procedures run serially within each partition, which removes locking for single-partition work. Datadog: Metrics are queried in aggregated time windows through the query API — individual raw data points cannot be extracted beyond Datadog's retention. Stacksync's field mapping accounts for these differences between Datadog and VoltDB without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Datadog and VoltDB records are not retained after a sync operation.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 324 integrations available for Datadog and VoltDB.