Apache HugeGraph vs Sparksee
Apache HugeGraph
hugegraph.apache.org
Sparksee
sparsity-technologies.comSide by side
| Figure | Apache HugeGraph | Sparksee |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 4 |
| Spec score · Graph Databases | 8.7 (#5) | 8.4 (#9) |
| Deployment | The Server can be deployed with Docker, a binary archive, a source build, or a legacy one-click deployment tool. | Sparksee runs from an application process against a database file, with no cluster or query server to provision. |
| Product | Apache HugeGraph is a graph system covering graph database, graph computing, and graph AI. | Sparksee is an embeddable graph database management system for representing and analysing complex relationships between entities. |
| Security | User authentication is disabled by default; the project advises enabling authentication and authorization, maintaining an IP allowlist, and avoiding direct public exposure of query endpoints in production. | The product page says Sparksee offers disk-level encryption to protect data if a device is stolen, lost, or sold. |
| Support | The project directs users to its Apache community, GitHub issues and discussions, developer mailing list, and Slack channel. | Trial applicants receive a build, sample project and access to an engineer for modelling questions; technical support is provided through the documentation and support sections. |
Plans
Sparksee
- Academic licenceFree
- Free trialPrice not published
- IndustryPriced on request
- StartupPriced on request
In their own words
Apache HugeGraph
Apache HugeGraph is an open-source graph system combining a graph database, graph computing, and graph AI. It supports Gremlin and Cypher/OpenCypher queries, a REST API, ACID transactions, graph algorithms, and vector search. HugeGraph-AI adds Python clients, graph machine-learning tools, and LLM tools for knowledge-graph construction and GraphRAG applications. Storage options include RocksDB for standalone use, HStore for distributed storage, and HBase. The project documents integrations with Spark and SeaTunnel and compatibility with Hadoop and Flink. Its toolchain provides graph loading, visualization, backup, restore, and migration; Hubble is a web interface for visualization and management. Documentation covers standalone deployments up to 2 TB and distributed deployments up to 1 PB. The project describes high-speed imports and millisecond-level real-time queries for hundreds of billions of graph data. It runs on Linux and macOS and can be self-hosted. The open-source plan costs nothing. Java 11 is recommended and required from version 1.5.0.
Sparksee
Sparksee is an embeddable graph database for applications that need to represent and analyse relationships among entities. It works against a database file from within an application process, so there is no cluster or query server to provision. The maker describes its compact bitmap-based representation as suited to graph computations in mobile and embedded environments. Built-in algorithms cover traversal, shortest paths, connectivity, community detection, and PageRank. Its API supports importing and exporting graph data, scripting, and Sparksee Cypher queries; Sparksee Algebra is also listed. API references cover.NET, Java, C++, Objective-C, Python, and openCypher. Sparksee supports ACID transactions, disk-level encryption, and recovery after database corruption. Keeping data on a user's device can support privacy-preserving apps and reduce reliance on cloud connectivity. Platforms include Android, iOS, Linux, macOS, and Windows, with API and self-hosted options. Eligible academic users can apply for a free licence; commercial licence pricing is on request.