EloqDoc

A MongoDB-compatible, high-performance, elastic, distributed document database.

Overview

EloqDoc is a high-performance, elastic, distributed transactional document database with MongoDB compability. Built on top of Data Substrate, it leverages a decoupled storage and compute architecture to deliver fast scaling, ACID transaction support, and efficient resource utilization.

EloqDoc eliminates the need for sharding components like mongos in MongoDB, offering a simpler, more powerful distributed database experience. It’s ideal for workloads requiring rapid scaling, high write throughput, and flexible resource management.

EloqDoc is a fork of MongoDB 4.0.3 that replaces the WiredTiger storage engine with the Eloq storage engine. It is distributed under the GNU Affero General Public License (AGPL).

Explore EloqDoc website for more details.

👉 Use Cases: web applications, ducument store, content management systems — anywhere you need MongoDB compatibility but demand distributed performance and elasticity.

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Key Features

⚙️ MongoDB Compatibility

Seamlessly integrates with MongoDB clients, drivers, and tools, enabling you to use existing MongoDB workflows with a distributed backend.

🌐 Distributed Architecture

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.
• Scales storage independently, conserving CPU resources for compute-intensive tasks.
• 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.

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Architecture Highlights

• Fast Scaling: 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.
• Write Optimization: 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.

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Run with Tarball

Download the EloqDoc tarball from the EloqData website.

Follow the instruction guide to set up and run EloqDoc on your local machine.

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Build from Source

Follow these steps to build and run EloqDoc from source.

1. Install Dependencies:

It is recommended to use our Docker image with pre-installed dependencies for a quick build and run of EloqDoc.

docker pull eloqdata/eloqdoc-build-ubuntu2404:latest

Or, you can manually run the following script to install dependencies on your local machine.

bash scripts/install_dependency_ubuntu2404.sh

2. Initialize Submodules

Fetch the code and initialize submodules:

git clone https://github.com/eloqdata/eloqdoc.git
git submodule update --init --recursive

3. Build EloqDoc

Configure and compile with optimized settings:

# Config RelWithDebInfo build for Eloq dependencies
cmake -S ./src/mongo/db/modules/eloq/ -B ./src/mongo/db/modules/eloq/release_build -DCMAKE_BUILD_TYPE=RelWithDebInfo
# Or Debug build
# cmake -S ./src/mongo/db/modules/eloq/ -B ./src/mongo/db/modules/eloq/debug_build -DCMAKE_BUILD_TYPE=Debug -DUSE_ASAN=ON

# Build Eloq dependencies
cmake --build src/mongo/db/modules/eloq/release_build/ -j6

# Build Mongo server
./scripts/build_mongo.sh RelWithDebInfo

# Build Mongo client
./scripts/build_mongo.sh Client

4. Set Up Storage Backend

EloqDoc supports multiple storage backends (e.g., Cassandra). Example setup with Cassandra:

wget https://archive.apache.org/dist/cassandra/4.1.8/apache-cassandra-4.1.8-bin.tar.gz
tar -zxvf apache-cassandra-4.1.8-bin.tar.gz
./apache-cassandra-4.1.8/bin/cassandra -f
# Verify Cassandra is running:
./apache-cassandra-4.1.8/bin/cqlsh localhost -u cassandra -p cassandra

5. (Optional) Config EloqDoc

Edit config/example.conf with example settings:

systemLog:
  verbosity: 2
  destination: file
  path: "~/eloqdoc_test/log.json"
  component:
    ftdc:
      verbosity: 0
net:
  port: 27017
  serviceExecutor: "adaptive"
  enableCoroutine: true
  reservedThreadNum: 2
  adaptiveThreadNum: 1
storage:
  dbPath: "~/eloqdoc_test"
  engine: "eloq"
  eloq:
    txService:
      coreNum: 2
      checkpointerIntervalSec: 10
      nodeMemoryLimitMB: 8192
      nodeLogLimitMB: 8192
      realtimeSampling: true
      collectActiveTxTsIntervalSec: 2
      checkpointerDelaySec: 5
    storage:
      keyspaceName: "mongo_test"
      cassHosts: 127.0.0.1
setParameter:
  diagnosticDataCollectionEnabled: false
  disableLogicalSessionCacheRefresh: true
  ttlMonitorEnabled: false

6. Start EloqDoc Node

mkdir ~/eloqdoc_test
scripts/run_with_config.sh RelWithDebInfo

Or

mkdir ~/eloqdoc_test
export LD_PRELOAD=/usr/local/lib/libmimalloc.so:/lib/libbrpc.so
./mongod --config config/example.conf

7. Connect to EloqDoc

./mongo --eval "db.t1.save({k: 1}); db.t1.find();"

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