DBMS > AnzoGraph DB vs. Splice Machine

System Properties Comparison AnzoGraph DB vs. Splice Machine

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Name

Description

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Graph DBMS
RDF store

Relational DBMS

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Trend Chart

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

Score	0.54
Rank	#239	Overall
	#112	Relational DBMS

Website

cambridgesemantics.com/anzograph

splicemachine.com

Technical documentation

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

splicemachine.com/how-it-works

Developer

Cambridge Semantics

Splice Machine

Initial release

2018

2014

Current release

2.3, January 2021

3.1, March 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL 3.0, commercial license 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
OS X
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C++
Java
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users, groups and roles according to SQL-standard

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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

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The 12 Best Graph Analytics Tools to Consider for 2025
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7 March 2025, DM News

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26 August 2021, The Register

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22 September 2023, InformationWeek

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