Jitsu

Capabilities

• Tag-level web capture Implementation is a script tag in the page, the same motion as installing Google Analytics, with SDKs and APIs for HTML, React, React Native, iOS, Android, npm packages, plain HTTP, pixels, and server-to-server calls. Consent management controls are documented alongside collection, so regulated tracking setups stay inside the same workflow.[1][2]

• Real-time warehouse delivery Events stream to ClickHouse, BigQuery, Snowflake, Redshift, Postgres, S3, GCS, and dozens of SaaS destinations, micro-batched or row-by-row depending on what each destination prefers. Data is ready for analysis in minutes rather than waiting on a daily load window.[1][2]

• Jitsu Functions JavaScript runs on every event to filter, transform, or enrich it before delivery, with access to npm packages and key-value storage, in-browser editing, and CLI deployment from your own TypeScript repo with tests and normal CI.[1][2]

• Segment Proxy A drop-in compatibility endpoint lets teams migrate off Segment by repointing their existing instrumentation instead of rewriting it, which removes re-instrumentation work from the migration.[1][2]

• Connector syncs Data can also be pulled into the warehouse from third-party sources through Airbyte-compatible connectors, covering the batch side next to event streaming. Sync frequency follows the plan: manual runs on Free, hourly on Business, and down to one-minute intervals on Enterprise.[1][2]

• Identity stitching and profiles A user identity graph and profile builder are assembled automatically from the event stream, joining anonymous and identified behavior so later analysis sees one user instead of fragments.[1][2]

• Live Events debugger Every event, function log, and destination write is visible as it happens, which compresses pipeline debugging from days to seconds and makes broken tracking obvious before stakeholders notice.[1]

• Programmatic operation A Management API, a configuration CLI, custom domains, schema management, deduplication, sessions, event backups, and an MCP server let developers and AI agents configure and operate workspaces without clicking through the UI.[1][2]

Who will love it

• If the warehouse is already the center of gravity, Jitsu slots in as the collection layer and keeps every event queryable with ordinary SQL. Functions and the Live Events debugger give those teams the control they expect over shaping and verifying the stream.[1][2]

• Event-volume pricing tracks data instead of audience size, and the free tier covers 200,000 active events a month, so costs scale with usage rather than headcount. High-traffic products with large anonymous audiences gain the most from this shape.[1][2]

• The MIT build runs entirely inside your own infrastructure, including on-premise and private-cloud deployments, which keeps regulated or sovereignty-sensitive data under your control. There are no usage limits on the self-hosted build, only your own infrastructure to operate.[1][2]

Who should think twice

• Jitsu delivers data, not insights; if nobody writes SQL or operates a BI tool, a managed no-code analytics product fits better. Event debugging and schema thinking still fall on the team.[1][2]

• A feature-complete self-hosted deployment requires running a Kubernetes cluster, and functions, profile building, and connector syncs all depend on it. Such teams should use Jitsu Cloud rather than self-hosting, or pick a fully managed alternative.[1]

• If the job is replicating SaaS databases and APIs on a schedule rather than capturing product events, a dedicated ELT tool such as Airbyte is the more direct choice. Jitsu's connector syncs complement event capture but do not replace a full ELT catalog.[1]

Fit and compatibility