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Package Overview

ArcadeDB Python provides a self-contained embedded package that runs the database directly in your Python process with a bundled JRE - no Java installation required!

The Package

| Package | Wheel Size | Installed Size | Java Required | Studio UI | Query Languages | |---------|-----------|------------------------------|---------------|----------------| | arcadedb-embedded | ~67MB | ~94MB | ❌ No | ✅ | SQL, OpenCypher |

Installation:

pip install arcadedb-embedded

Requirements: Python 3.10–3.14 (packaged; primary testing on 3.12) - No Java installation needed!

What's Inside

The package includes everything you need:

  • ArcadeDB JARs (~31MB, uncompressed): Core database plus the optional server/Studio stack
  • Bundled JRE (~63MB, uncompressed): Platform-specific Java 25 runtime (via jlink)

Current Linux x86_64 package info: ~67MB compressed wheel, ~63MB JRE, ~31MB JARs, and ~94MB installed.

These numbers are measured from the built wheel file and the extracted site-packages/arcadedb_embedded/ directory, and they vary by platform and version.

Platform Support

Pre-built platform-specific wheels are available for 4 platforms. Sizes stay in the same ballpark across platforms, but vary slightly by platform and version (see size breakdown below).

Key Features:

  • ✅ All platforms use platform-specific wheels (not universal)
  • ✅ pip automatically selects the correct wheel for your system
  • ✅ Each platform has its own bundled JRE optimized for that architecture
  • ✅ Full bindings suite passes on every platform build
  • ✅ Built on native runners (no emulation) for optimal performance

What's Included

Core Features:

  • ✅ No Java Installation Required: Platform-specific JRE bundled (~63MB uncompressed)
  • ✅ Core Database: All models (Graph, Document, Key/Value, Vector, Time Series)
  • ✅ Query Languages: SQL, OpenCypher (all included)
  • ✅ Vector Search: Graph-based indexing for embeddings
  • ✅ Data Import: CSV, XML, and ArcadeDB JSONL import
  • ✅ Server Mode: Optional in-process HTTP server
  • ✅ Studio Web UI: Visual database explorer and query editor

Optimized:

  • Some components are excluded to optimize package size (e.g., the gRPC wire protocol). See scripts/jar_exclusions.txt in the repository for the full list.
  • The bundled server is in-process, so its lifetime is your Python process's. For a standalone server, HA/replication, TLS, or the Postgres/Redis/Mongo wire protocols, run the official ArcadeDB server — see Access Methods.

Use Cases

Perfect for:

  • Production Python applications
  • Cloud deployments (no Java setup needed!)
  • Docker containers
  • Desktop applications
  • Multi-model database needs (Graph, Document, Vector, Time Series)
  • Any scenario requiring SQL or OpenCypher queries
  • Development and debugging (with Studio UI)

Accessing Studio UI

from arcadedb_embedded import create_server

# Start HTTP server with Studio UI
server = create_server("./databases", root_password="password123")
server.start()

# Studio UI available at the URL below (port 2480 by default)
print(server.get_studio_url())

# When done
server.stop()

Studio in Browser

Once the server starts, open the printed URL to reach the Studio UI. Studio ships as static assets with no executable code, so it costs disk and nothing else until a browser actually requests it.

Import Statement

The import is always:

import arcadedb_embedded as arcadedb

Simple and consistent across all platforms!

Size Breakdown

Current sizes are ballpark values and can move with ArcadeDB, the bundled JRE, the target platform, and filesystem overhead after installation:

  • Wheel (compressed): ~67MB
  • Installed package: ~94MB

Components (uncompressed):

  • ArcadeDB JARs: ~31MB (63 JARs, of which 12 are the optional server stack at 7.65MB)
  • Bundled JRE: ~63MB (platform-specific Java 25 runtime via jlink, 16 modules)

Optimizations:

  • The gRPC wire protocol is excluded; server and Studio are included
  • See scripts/jar_exclusions.txt in repository for details

Installation Tips

Check Installed Package

import arcadedb_embedded as arcadedb
print(f"Version: {arcadedb.__version__}")

# Verify database works
with arcadedb.create_database("./test") as db:
    result = db.query("sql", "SELECT 1 as test")
    print(f"Database working: {result.first().get('test') == 1}")

Platform Detection

pip automatically selects the correct platform-specific wheel:

# On Linux x64 for Python 3.12, installs: arcadedb_embedded-X.Y.Z-cp312-cp312-manylinux_2_34_x86_64.whl
# On macOS ARM64 for Python 3.12, installs: arcadedb_embedded-X.Y.Z-cp312-cp312-macosx_11_0_arm64.whl
# On Windows x86_64 for Python 3.12, installs: arcadedb_embedded-X.Y.Z-cp312-cp312-win_amd64.whl
# etc.

You can verify which platform you're on:

import platform
print(f"System: {platform.system()}")
print(f"Machine: {platform.machine()}")
print(f"Python: {platform.python_version()}")

Next Steps