DBMS > AnzoGraph DB vs. Stardog vs. Vitess

System Properties Comparison AnzoGraph DB vs. Stardog vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.21
Rank	#308	Overall
	#26	Graph DBMS
	#15	RDF stores

Score	1.59
Rank	#136	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.93
Rank	#192	Overall
	#88	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.stardog.com

vitess.io

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.stardog.com

vitess.io/docs

Developer

Cambridge Semantics

Stardog-Union

The Linux Foundation, PlanetScale

Initial release

2018

2010

2013

Current release

2.3, January 2021

7.3.0, May 2020

15.0.2, December 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux

Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

with proprietary extensions

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C++
Java
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions and aggregates, HTTP Server extensions in Java

yes

proprietary syntax

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency in HA-Cluster

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

not needed in graphs

yes

relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

AnzoGraph: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

Knowledge graph evolution: Platforms that speak your language
30 January 2020, ZDNet

The 12 Best Graph Databases to Consider for 2025
29 March 2021, Solutions Review

provided by Google News

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

3 Cloud-Native Database Tools From CNCF
26 July 2022, Cloud Native Now

PlanetScale Announces $30M Series B Funding to Accelerate Adoption of Instantly Provisioned and Infinitely Scalable Database
23 June 2021, Business Wire

Update CNCF’s Vitess Scales MySQL with the Help of Kubernetes
29 March 2022, InApps Technology

PlanetScale review: Horizontally scalable MySQL in the cloud
1 September 2021, InfoWorld

provided by Google News

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