Show HN: EloqDoc: MongoDB-compatible doc DB with object storage as first citizen

EloqDoc A MongoDB API compatible , high-performance, elastic, distributed document database. Overview EloqDoc is a high-performance, distributed transactional document database with MongoDB API compatibility. Its breakthrough architecture, powered by Data Substrate, redefines the balance between cost, scalability, and performance for real-world document workloads. Unlike MongoDB, which relies on three replica-set nodes for durability, EloqDoc treats cloud object storage as a first-class citizen. Durable, cross–availability zone (AZ) object storage serves as the persistent foundation, while local NVMe caching accelerates reads. Recent updates are written to a decoupled redo log component. This architecture minimizes write latency while maintaining strong consistency and durability. The result is a cloud-native, storage-centric deployment model: EloqDoc typically runs a single compute replica with storage-level high availability, orchestrated by Kubernetes for automatic failover. This approach cuts infrastructure costs, avoids redundant CPU and memory overhead, and delivers higher throughput across mixed read/write workloads. Explore EloqDoc for more details, or skip ahead to the Key Features section for a deeper breakdown. You can also experience the managed cloud version at EloqCloud. 👉 Use Cases: web applications, document stores, content platforms—anywhere you need MongoDB API compatibility and expect distributed performance and elasticity. Key Features ⚙️ MongoDB API Compatibility Seamlessly integrates with MongoDB clients, drivers, and tools, enabling you to use existing MongoDB workflows with a distributed backend. 🗃️ Tiered Storage Architecture EloqDoc seamlessly manages hot and cold data across memory, local NVMe cache, and object storage. Since NVMe storage is ephemeral and lost when a node crashes, EloqDoc uses it strictly as a cache for object storage. This design ensures that all data remains safe and durable in cross-AZ object storage while still benefiting from NVMe-level performance for frequently accessed data. 🌐 Truely Distributed Database Supports multiple writers and fast distributed transactions, ensuring high concurrency and fault tolerance across a cluster without sharding complexity. 🔄 Elastic Scalability Scales compute and memory 100x faster than traditional databases by avoiding data movement on disk. than traditional databases by avoiding data movement on disk. Scales storage independently, so CPU resources remain constant when data volume grows but traffic stays the same. Scales redo logs independently to optimize write throughput. 🔥 High-Performance Transactions Delivers ACID transaction support with especially fast distributed transactions, making it suitable for mission-critical applications. 🔒 Simplified Distributed Design Operates as a distributed database without requiring a sharding coordinator (e.g., mongos ), reducing operational complexity and overhead. Architecture EloqDoc is a decoupled, distributed database built on Data Substrate, the innovative new database foundation developed by EloqData. Each EloqDoc instance includes a frontend, compatible with the MongoDB protocol, deployed together with the core TxService to handle data operations. A logically independent LogService handles Write Ahead Logging (WAL) to ensure persistence, while a Storage Service manages memory state checkpoints and cold data storage. This architecture enable EloqDoc to support: Fast Scaling : Compute and memory scale independently without disk data movement, enabling rapid elasticity for dynamic workloads. : Compute and memory scale independently without disk data movement, enabling rapid elasticity for dynamic workloads. Storage Flexibility : Storage scales separately from compute, optimizing resource allocation and reducing waste. : Storage scales separately from compute, optimizing resource allocation and reducing waste. Write Optimization : Independent redo log scaling boosts write throughput, ideal for high-velocity data ingestion. : Independent redo log scaling boosts write throughput, ideal for high-velocity data ingestion. No Sharding Overhead: Distributes data natively across the cluster, eliminating the need for additional sharding components. Benchmark All tests were conducted on AWS EC2 i4i.4xlarge instances, featuring 16 vCPUs, 128 GB RAM, and high-performance local NVMe storage. We evaluated EloqDoc against MongoDB Atlas across representative deployment scenarios, ranging from fully in-memory workloads to cases where the working set exceeds cache capacity. Both systems were benchmarked using identical client concurrency levels and dataset characteristics to ensure fairness and reproducibility. Key takeaways EloqDoc sustained up to 60% higher throughput than MongoDB Atlas for mixed 1:1 read/write workloads when the active dataset was fully cached. For read-heavy applications, EloqDoc delivered roughly 60% higher peak throughput while maintaining lower latency across the entire concurrency range. When the workload required frequent disk accesses, EloqDoc’s local NVMe cache + object storage design preserved performance and availability, whereas Atlas’s EBS-backed tier became IO-bound. Fully Cached Results Mixed read/write (1:1) – EloqDoc maintained higher throughput under heavy contention and peaked at roughly 60% more operations per second than Atlas. Read-only – EloqDoc achieved high throughput even at moderate concurrency, sustaining about 60% higher throughput compared with Atlas. Low Cache Hit Rate Results For datasets that exceed available memory, we configured both systems to serve 150 million documents, forcing regular cache misses. EloqDoc leverages local NVMe as a write-back cache layered over durable object storage. This architecture delivered hundreds of thousands of IOPS while keeping data fully resilient. In contrast, the Atlas deployment backed by network EBS volumes saturated its IO budget, leading to noticeably lower throughput and higher tail latency. We will publish more detailed benchmarks in future. Quick Start Try EloqDoc-RocksDB Using Official Package Step-1, download the official package for EloqDoc-RocksDB. Please select the package that matches your operating system. wget -c https://download.eloqdata.com/eloqdoc/eloqdss_rocksdb/eloqdoc-0.2.6-ubuntu22-amd64.tar.gz All released package can be found at download page. Step-2, uncompress the package to your $HOME . mkdir $HOME /eloqdoc-rocksdb && tar -xf eloqdoc-0.2.6-ubuntu22-amd64.tar.gz -C $HOME /eloqdoc-rocksdb After uncompress the package, you should see three directories: bin , lib , and etc . bin contains all executable files, lib contains all dependencies, and etc contains an example configuration file eloqdoc.conf . Switch to eloqdoc-rocksdb to verify that. cd $HOME /eloqdoc-rocksdb && ls Step-3, create a data directory and a log directory. Simply place them under $HOME/eloqdoc-rocksdb . mkdir db logs Step-4, modify etc/eloqdoc.conf . Assume your $HOME is /home/eloq , then Set systemLog.path to /home/eloq/eloqdoc-rocksdb/logs/eloqdoc.log . to . Set storage.dbPath to /home/eloq/eloqdoc-rocksdb/db . Step-5, start the server with: ./bin/eloqdoc --config ./etc/eloqdoc.conf Step-6, open another terminal and run mongo client. ./bin/eloqdoc-cli --eval " db.t1.save({k: 1}); db.t1.find(); " It should output connecting to: mongodb://127.0.0.1:27017 Implicit session: session { " id " : UUID( " 288393c1-aff6-4a84-ad46-dee6691b361d " ) } { " _id " : ObjectId( " 68493ec41cc981ea926ec094 " ), " k " : 1 } Try EloqDoc-RocksDBCloud Using Official Package Step-1, download the official package for EloqDoc-RocksDBCloud. Please select the package that matches your operating system. wget -c https://download.eloqdata.com/eloqdoc/rocks_s3/eloqdoc-0.2.6-ubuntu22-amd64.tar.gz All released package can be found at download page. Step-2, uncompress the package to your $HOME . mkdir $HOME /eloqdoc-rocksdbcloud && tar -xf eloqdoc-0.2.6-ubuntu22-amd64.tar.gz -C $HOME /eloqdoc-rocksdbcloud After uncompress the package, you should see three directories: bin , lib , and etc . bin contains all executable files, lib contains all dependencies, and etc contains an example configuration file eloqdoc.conf . Switch to eloqdoc-rocksdbcloud to verify that. cd $HOME /eloqdoc-rocksdbcloud && ls Step-3, create a data directory and a log directory. Simply place them under $HOME/eloqdoc-rocksdbcloud . mkdir db logs Step-4, start a S3 emulator, takes minio as an exmaple. cd $HOME mkdir minio-service && cd minio-service wget https://dl.min.io/server/minio/release/linux-amd64/minio chmod +x minio ./minio server ./data By default, minio listens on http://127.0.0.1:9000 , whose default credentials is minioadmin:minioadmin ,. Step-5, go back to $HOME/eloqdoc-rocksdbcloud and modify etc/eloqdoc.conf . Assume your $HOME is /home/eloq . cd $HOME /eloqdoc-rocksdbcloud Set systemLog.path to /home/eloq/eloqdoc-rocksdbcloud/logs/eloqdoc.log . to . Set storage.dbPath to /home/eloq/eloqdoc-rocksdbcloud/db . to . etc/eloqdoc.conf has configured minio as its cloud storage, and needs no modification. Step-6, start the server with: ./bin/eloqdoc --config ./etc/eloqdoc.conf Step-7, open another terminal and run mongo client. ./bin/eloqdoc-cli --eval " db.t1.save({k: 1}); db.t1.find(); " It should output connecting to: mongodb://127.0.0.1:27017 Implicit session: session { " id " : UUID( " 288393c1-aff6-4a84-ad46-dee6691b361d " ) } { " _id " : ObjectId( " 68493ec41cc981ea926ec094 " ), " k " : 1 } Advanced Topics Follow compile tutorial to learn how to compile EloqDoc-RocksDB and EloqDocRocksDBCloud from scratch. Follow deploy cluster to learn how to deploy an EloqDoc-RocksDBCloud cluster. Follow configuration description to learn major configuration parameters. 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