Two-way sync
Changes in Apache Cassandra or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Cassandra and Yellowbrick in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Apache Cassandra's rows in Yellowbrick, 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 Apache Cassandra where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Apache Cassandra sync into Yellowbrick in real time, and result tables in Yellowbrick sync back into Apache Cassandra, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Yellowbrick and keep Apache Cassandra focused on its operational workload.
Rows from Apache Cassandra land in Yellowbrick as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Yellowbrick sync into Apache Cassandra, where whatever reads from that database gets them without querying the warehouse.
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 | Yellowbrick objects | |
|---|---|---|
| Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. | Schemas Namespaces used to organize synced datasets by source or domain. | |
| Secondary Indexes Optional indexes that allow filtered reads outside the partition key. | Tables Columnar MPP tables; the primary targets for warehouse syncs. | |
| User-Defined Types Composite column types that syncs must flatten or map to structured fields. | Views Logical views used to shape reads for BI and downstream syncs. | |
| Collections List, set, and map columns handled with type-aware field mapping. | Users and Roles Access-control objects that govern what a sync service account can read and write. | |
| Counters Increment-only counter columns, usually read-only in syncs. | Databases Top-level containers for schemas and tables. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–Yellowbrick connection.
Changes in Apache Cassandra or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Cassandra or Yellowbrick 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 Yellowbrick record.
Track your Apache Cassandra ⇄ Yellowbrick sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Cassandra and Yellowbrick.
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 Yellowbrick 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 Yellowbrick 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 Yellowbrick: authenticate both systems, choose the objects to sync (such as Apache Cassandra's Materialized Views and Secondary Indexes), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Yellowbrick side: Databases, Schemas, Tables, Views, plus custom fields where Yellowbrick exposes them. On the Apache Cassandra side: Counters, Keyspaces, Tables, Partitions and Rows. Stacksync auto-detects both schemas and converts types between the two systems.
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 Apache Cassandra and Yellowbrick: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Yellowbrick and keep Apache Cassandra focused on its operational workload.
Apache Cassandra: CQL over the Cassandra native binary protocol. Authentication: Database credentials (password authenticator); TLS and role-based grants where configured. Yellowbrick: SQL wire protocol (PostgreSQL-compatible) with JDBC/ODBC drivers; bulk loading via the ybload utility. Authentication: Database credentials, with LDAP and Kerberos options in enterprise deployments. Stacksync manages authentication, retries, and rate limits on both sides.
Yellowbrick: The front end is PostgreSQL-compatible, so standard Postgres drivers and SQL tooling connect without custom clients. Apache Cassandra: CDC is enabled per table and surfaces changes through commit-log segments, which is how log-based connectors consume Cassandra changes. Stacksync's field mapping accounts for these differences between Apache Cassandra and Yellowbrick without custom code.
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 386 integrations available for Apache Cassandra and Yellowbrick.