DataStax Enterprise vs Raphtory

Both are property graph databases. DataStax Enterprise (2016-04, Proprietary, Java) ranks #69 this month; Raphtory (2020-12, GPL-3.0, Rust) ranks #24.

Attribute DataStax Enterprise #69 ▲1 Growing Raphtory #24 ▼7 Strong
At a glance
Rank #69#24
Score 43.355.6
GitHub stars —650
Popularity 46.753.3
Activity 43.671.3
Community 34.730.3
Research 50.470.7
Fundamentals
Description A property graph database built on Apache Cassandra, forked from the Titan graph database. Uses TinkerPop for graph traversal and includes DataStax Studio for interactive querying and visualization.An in-memory temporal graph database written in Rust with Python and Rust APIs. Tracks graph changes over time with time-traveling queries across historical states. Supports multilayer graph modeling, built-in graph algorithms, and full-text search. Includes a GraphQL server with a bundled exploration UI.
Vendor IBMPometry
Model Property GraphProperty Graph
Kind databasedatabase
Category EstablishedEmerging
First released 2016-042020-12
Status activeactive
License ProprietaryGPL-3.0
Written in JavaRust
Query languages Gremlin, CQLGraphQL
gdotv support yesno

Feature scores — not surveyed for Raphtory

Feature DataStax EnterpriseRaphtory
Community & Business
Active development ✓—
Commercial support ✓—
Live community 0.25—
Open Source ·—
Pricing ·—
Trendiness 0.25—
Deployment
Containerization ✓—
Work as dedicated instance ✓—
Work as embedded ·—
Testing in-memory version ·—
Platform
Operating on Linux ✓—
Operating on Windows 0.5—
SaaS offering ✓—
Operations
Automatic updates ·—
Client side caching ·—
Data versioning support ·—
Live backups ✓—
Distribution
Cluster Re-balancing ✓—
Data Distribution ✓—
High-Availability ✓—
Query Distribution ✓—
Replication support ✓—
Developer Experience
Data types defined ✓—
Logging/Auditing ✓—
Object-Graph Mapper ✓—
Reactive programming ·—
Documentation up-to-date 0.5—
Binary protocol ✓—
CLI ✓—
GUI ✓—
Data Model
Multi-database ·—
Graph-native data ·—
REST API ·—
Query Language ✓—
Transactions
Granular locking ·—
Multiple isolation levels ·—
Read committed transaction ·—
Transaction support ·—
Schema & Security
Constraints ✓—
Schema support ✓—
Secondary indexes ✓—
Server side procedures ·—
Triggers ✓—
Authentication ✓—
Authorization ✓—
Data encryption ✓—