DBMS > AnzoGraph DB vs. CrateDB vs. VoltDB

System Properties Comparison AnzoGraph DB vs. CrateDB vs. VoltDB

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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

Distributed Database based on Lucene

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
RDF store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.23
Rank	#297	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.68
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#12	Vector DBMS

Score	1.37
Rank	#156	Overall
	#72	Relational DBMS

Website

cambridgesemantics.com/anzograph

cratedb.com

www.voltdb.com

Technical documentation

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

cratedb.com/docs

docs.voltdb.com

Developer

Cambridge Semantics

Crate

VoltDB Inc.

Initial release

2018

2013

2010

Current release

2.3, January 2021

5.8.1, August 2024

11.3, April 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X

for development

Data scheme

Schema-free and OWL/RDFS-schema support

Flexible Schema (defined schema, partial schema, schema free)

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

only a subset of SQL 99

APIs and other access methods

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

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions (Javascript)

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Configurable replication on table/partition-level

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

Eventual Consistency
Read-after-write consistency on record level

Foreign keys

Referential integrity

not needed in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

rights management via user accounts

Users and roles with access to stored procedures

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More resources

Recent citations in the news

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

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

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

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

provided by Google News

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16 May 2017, Business Wire

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Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge
15 April 2021, GlobeNewswire

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31 August 2021, PR Newswire

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

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16 October 2023, YourStory

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