EloqData

EloqData is devloping a converged, scalable, high-performance multi-model database to support the diverse needs of modern AI powered applications

[EloqData @Eloq_Data]

EloqCloud for EloqDoc: 10X Cheaper Document DBaaS

After the successful launch of EloqCloud for EloqKV, today we are excited to announce EloqCloud for EloqDoc — our new MongoDB-compatible document database built for the cloud era.

EloqCloud for EloqDoc brings a breakthrough architecture that redefines the balance between cost, scalability, and performance for document workloads.

Start for Free and experience the next-generation document database —
MongoDB-compatible, object storage first, high performance and cost effective. https://t.co/sGBqKNbdF3

Learn more https://t.co/xYRdH1DUPq

[EloqData @Eloq_Data]

Stop Redis hot key failures. EloqKV scales read replicas via storage, not CPU. Fast & stable.

[EloqData @Eloq_Data]

Experience EloqData's innovative solution for cross-region caching, ensuring superior performance, automated failover, and lower TCO with no external dependencies.

Ready to build a resilient, cost-effective caching service?
Follow us to learn more.

[EloqData @Eloq_Data]

@InfluxDB Great application. Supporting both real-time ingestion for the twin and large-scale scans for ML training on the same backend is a classic challenge. How are you seeing teams architect for these different access patterns without contention?

[EloqData @Eloq_Data]

@mariadb Curious how this architectural vision extends to modern cloud infrastructure. For example, how does MariaDB's approach to logging and durability adapt when running with a decoupled object storage layer?

[EloqData @Eloq_Data]

@MySQL Interesting approach. Does the REST service layer participate in the underlying transaction model, or is it more of a CRUD wrapper? Curious how atomicity is handled for complex operations via the API.

[EloqData @Eloq_Data]

@axboe Great to see continued optimization in the I/O path. For decoupled storage architectures, improvements here have a cascading effect, especially when network and local storage I/O compete for resources.

[EloqData @Eloq_Data]

@alighodsi Congrats on the fundraise. The focus on a serverless database for agents is spot on. We've seen that balancing the low latency agents need with the scalability of a decoupled backend is key. An NVMe cache over object storage is a useful pattern for this.

[EloqData @Eloq_Data]

@InfluxDB The move to Parquet on object storage is a powerful pattern.

[EloqData @Eloq_Data]

@InfluxDB Custom plugins offer a lot of flexibility.

[EloqData @Eloq_Data]

@PostgreSQL Integrating AI models directly into the database is a powerful pattern. How is resource management handled?

[EloqData @Eloq_Data]

@oraclebase A long list of known issues always brings durability and recovery paths to mind. We've seen architectures that treat object storage as the source of truth lead to more predictable and simpler recovery.

[EloqData @Eloq_Data]

@SingleStoreDB @DOTGroupLtd Good to see this focus on analytics modernization. With cloud transformation projects, are you seeing common architectural patterns emerge? We've found decoupling compute and storage is a frequent starting point.

[EloqData @Eloq_Data]

@erikdarlingdata Interesting video. Curious how SQL Server 2025 will handle resource isolation for AI workloads running alongside transactional ones. Protecting core OLTP latency is a key challenge with mixed-use systems.

[EloqData @Eloq_Data]

@Yugabyte Good points. A key part of resilience is also predictable recovery. We've seen that decoupling compute from storage, with durability anchored in object storage, helps simplify failure domains.

[EloqData @Eloq_Data]

@ycombinator @ryolu_ @aaron_epstein The focus on rapid prototyping is spot on. For dev tools, especially in the data space, reducing setup friction is critical. A developer should be able to run a real PoC in minutes, not days.

[EloqData @Eloq_Data]

@InfluxDB Sustaining that frame rate requires predictable tail latency from the database. In our work with industrial systems, decoupling storage and using NVMe as a pure cache has been key to smoothing out query performance.

[EloqData @Eloq_Data]

@InfluxDB Good point on handling both workloads. Curious how the query execution layer handles this split—does it need to be tier-aware to optimize queries that span both real-time and historical data?

[EloqData @Eloq_Data]

@CockroachDB The best feeling. This level of confidence often comes down to the durability model. When compute nodes are effectively stateless caches, rolling them out becomes a non-event.

[EloqData @Eloq_Data]

@erikdarlingdata lol

[EloqData @Eloq_Data]

@mariadb Hot take for 2026: Databases built with object storage as the source of truth become the default. Using local NVMe purely as a cache, not for primary durability, simplifies recovery and scaling.