3 Best Open Source Amazon Neptune Alternatives
A curated collection of the 3 best open source and self-hosted alternatives to Amazon Neptune in 2026.
Looking for a free, privacy-friendly, or self-hosted replacement for Amazon Neptune in 2026? The top open-source alternative is Neon Postgres — Postgres backends for apps and agents.
Other highly rated open-source Amazon Neptune alternatives include OceanBase and Memgraph.
Postgres backends for apps and agents
Neon is a serverless Postgres database platform built for modern applications and AI agents. It combines Lakebase Postgres with integrated authentication, serverless functions, S3-compatible storage, and an AI gateway into a unified backend. - Lakebase Postgres: Storage-compute separation for instant scaling and branching - Built-in Auth: Authentication integrated directly into your database - Serverless Functions: Compute next to your data for low-latency operations - Object Storage: S3-compatible storage that branches alongside your database - AI Gateway: Single API for frontier and open-source AI models - Autoscaling: Automatic instance sizing based on workload demands - Branching: Faster Postgres workflows with instant database branches - Instant Restore: Recover from mistakes in seconds - Vector & Hybrid Search: Advanced search capabilities for AI applications Neon is a fully managed cloud service built on Lakebase Postgres architecture. While the core technology is open source (available at https://github.com/neondatabase/neon), the managed service includes additional features like the AI gateway, authentication, and advanced tooling. The platform is designed for high availability with automatic failover and regional replication. For self-hosting the open-source components, documentation is available in the GitHub repository, though the full managed experience requires Neon's cloud infrastructure.
Unified distributed database for transactions, analytics, and AI
OceanBase is a unified distributed database designed to handle transactional, analytical, and AI workloads with ultra-fast performance. It maintains world records in both TPC-C (OLTP) and TPC-H (analytics) benchmarks, demonstrating its exceptional scalability and efficiency. - Unified Database: Supports OLTP, real-time analytics, and AI workloads in a single system - World-Record Performance: Holds TPC-C and TPC-H benchmark records for speed and scalability - Global Deployment: Enables multi-cloud and global application deployment with active geo-redundancy - Elastic Scaling: Automatically scales to handle peak traffic demands without downtime - Mission-Critical Reliability: Powers critical systems for 400+ enterprises including Alipay - Open Source Community Edition: Free, open-source distributed database available - AI Lakebase: Specialized version for operational data, real-time analytics, and AI applications - Database Consolidation: Supports multi-tenant architectures for efficient resource utilization OceanBase offers multiple deployment options: - OceanBase Cloud: Fully managed cloud service for easy deployment and scaling - OceanBase Enterprise: Self-hosted version for on-premises or private cloud deployment - Community Edition: Open-source version available on GitHub for self-hosting - OceanBase seekdb: Open-source AI-native search database The database is compatible with standard SQL interfaces and provides connectors for various programming languages and frameworks. Comprehensive documentation and training resources are available for all deployment options.
High-performance in-memory graph database
Memgraph is a high-performance, in-memory graph database designed for real-time analytics and AI workloads. It enables organizations to process and query connected data at scale with millisecond latency, making it ideal for fraud detection, knowledge graphs, logistics optimization, and AI agent memory. - Real-time graph processing: In-memory architecture for sub-millisecond query responses - Cypher compatibility: Full support for Neo4j's Cypher query language - Vector search integration: Native support for semantic search and AI workloads - GraphRAG capabilities: Structured context for AI applications - High availability & security: Enterprise-grade features including encryption and role-based access control - ZeroETL: Direct query capabilities without traditional ETL pipelines - Multi-model support: Handles both property graphs and vector embeddings - Developer tools: Memgraph Lab (visual interface), Python drivers, and NetworkX compatibility Memgraph offers both cloud and self-hosted deployment options. The open-source core is available on GitHub, with enterprise features requiring a license. Supports Docker, Kubernetes, and bare-metal installations. Compatible with major cloud providers and offers managed services for production deployments.
About Amazon Neptune
Amazon Neptune is a fast, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. Neptune supports both Property Graph and RDF graph models and provides APIs for Gremlin, SPARQL, and openCypher query languages.
Key Features of Amazon Neptune
- Fully Managed: Automated provisioning, patching, backup, and recovery with no downtime
- High Performance: Optimized for low-latency queries on large-scale graph datasets
- Multiple Graph Models: Supports Property Graph (Gremlin, openCypher) and RDF (SPARQL) models
- Scalability: Automatically scales compute and memory resources based on workload demands
- Security: Built-in encryption, VPC isolation, and IAM-based access control
- High Availability: Multi-AZ deployments with automatic failover
- Integration: Seamless integration with AWS analytics and machine learning services
- Cost-Effective: Pay-as-you-go pricing with no upfront costs or long-term commitments
Tech / Self-Hosting
Amazon Neptune is a fully managed AWS service and cannot be self-hosted. It runs within AWS's global infrastructure and provides regional endpoints for high availability. Neptune is designed for applications requiring persistent, low-latency graph queries with automatic scaling and maintenance.