Prometheus vs Tigris
Side-by-side trajectory, velocity, and editorial themes.
Prometheus enters 3.12 RC while running a coordinated security backport across the 3.5 LTS line.
Prometheus published a 3.12.0 release candidate with PromQL and Service Discovery additions, TSDB performance work, and security fixes for a remote-write denial-of-service and a STAC secret leak. In the same window, 3.11.3 and 3.5.3 shipped coordinated security fixes for snappy decoding, AzureAD client_secret handling, and an old-UI XSS, and the prior 3.11.2/3.5.2 pair fixed a metric-name XSS in the web UI. The project is clearly maintaining 3.5 as a long-term branch alongside the active 3.x line.
Cadence is dominated by responsible-disclosure security work, with feature additions concentrated in the upcoming 3.12 release. The fact that 3.5 keeps receiving coordinated backports months after 3.11 suggests Prometheus is informally treating 3.5 as a stable LTS for environments that cannot upgrade quickly.
Expect 3.12.0 to ship final within a few weeks given the RC has already landed, and a 3.5.4 backport to follow the next security disclosure rather than the next feature batch.
Tigris turns its object store into agent infrastructure with Agent Kit, agent-shell, and durable global streams.
Tigris's release stream is a sustained product-marketing push around AI-agent storage primitives. Agent Kit landed as a TypeScript SDK exposing bucket forks, workspaces, checkpoints, and event coordination. agent-shell put a virtual bash environment with persistent storage in front of those primitives. Durable global streams via S2 Lite extended the object store into a streaming substrate suitable for per-agent reasoning traces. Around the launches, case studies and tutorials (Basic Memory, the $10 self-updating knowledge base) make the pitch concrete.
Tigris is staking a position that the right substrate for AI agents is not a database, vector store, or queue — it is a globally-distributed, fork-able object store. Each blog and SDK in this batch reinforces that thesis from a different angle: storage as message queue, fork-per-agent sandboxing, storage-protected agent containment, streams for reasoning traces. The competitive map being drawn includes R2, S3 Express, Backblaze, and the agent-runtime vendors (Modal, E2B), not other databases.
Expect a managed Vector or Lance-index surface on top of buckets to compete more directly with Turbopuffer and Pinecone, and a Python counterpart to the @tigrisdata/agent-shell TypeScript runtime to widen the agent-developer surface area.
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