Two-way sync
Changes in Apache Cassandra or Datadog instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Cassandra and Datadog in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Apache Cassandra 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 User-Defined Types, Collections, Counters, Keyspaces in Apache Cassandra with Metrics, Incidents, Service Level Objectives, Hosts 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 Apache Cassandra, so provisioning and de-provisioning flow from one source.
A new or changed row in Apache Cassandra 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 Apache Cassandra 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.
| Apache Cassandra objects | Datadog objects | How this pairing syncs | |
|---|---|---|---|
| User-Defined Types Composite column types that syncs must flatten or map to structured fields. | 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. | User-Defined Types is specific to Apache Cassandra and Service Level Objectives to Datadog — each maps to any object or custom field on the other side. | |
| Collections List, set, and map columns handled with type-aware field mapping. | 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. | Collections is specific to Apache Cassandra and Hosts to Datadog — each maps to any object or custom field on the other side. | |
| Counters Increment-only counter columns, usually read-only in syncs. | 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. | Counters is specific to Apache Cassandra and Monitors to Datadog — each maps to any object or custom field on the other side. | |
| Keyspaces Top-level namespaces with replication settings that scope a sync connection. | Logs Log events searched via the v2 Logs search endpoint by time window and submittable through the log intake API; commonly streamed to a warehouse for retention beyond Datadog's storage period. | Keyspaces is specific to Apache Cassandra and Logs to Datadog — each maps to any object or custom field on the other side. | |
| Tables Wide-column tables addressed by partition key, the unit of row-level sync. | Events The event stream (deploys, alerts, comments) searched via the v2 Events endpoint and posted via POST /api/v1/events; used to correlate deploy and incident timelines or to publish deploy and pipeline events into Datadog. | Tables is specific to Apache Cassandra and Events to Datadog — each maps to any object or custom field on the other side. | |
| Partitions and Rows Records located by partition and clustering keys during reads and upserts. | 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. | Partitions and Rows is specific to Apache Cassandra and Dashboards to Datadog — 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.
DetectionChanges in Apache Cassandra are captured at the source via change data capture — no polling loop against its API. Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns.
DeliveryEach detected change is written to Datadog through its API, with automatic retries and rate-limit backoff.
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 written to Apache Cassandra through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–Datadog connection.
Changes in Apache Cassandra or Datadog instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Cassandra or Datadog data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Cassandra or Datadog record.
Track your Apache Cassandra ⇄ Datadog sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Cassandra and Datadog.
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 Apache Cassandra and Datadog 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 Apache Cassandra and Datadog 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 Apache Cassandra and Datadog: authenticate both systems, choose the objects to sync (such as Apache Cassandra's User-Defined Types and Collections), map fields visually, and changes propagate both ways in milliseconds — no code required.
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 Apache Cassandra and Datadog records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Cassandra and Datadog connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Cassandra–Datadog integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Cassandra and Datadog. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Apache Cassandra: Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns. On Datadog: Polling with time-windowed search queries on Logs and Events (timestamp cursor); monitor alerts can also push via the Webhooks notification integration. No modified-date CDC on mutable objects. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Cassandra side: User-Defined Types, Collections, Counters, Keyspaces, plus custom fields where Apache Cassandra exposes them. On the Datadog side: Metrics, Incidents, Service Level Objectives, Hosts. Stacksync auto-detects both schemas and converts types between the two systems.
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 309 integrations available for Apache Cassandra and Datadog.