DBMS > AnzoGraph DB vs. IBM Db2 vs. Riak TS vs. SQLite

System Properties Comparison AnzoGraph DB vs. IBM Db2 vs. Riak TS vs. SQLite

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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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Time Series DBMS

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	123.05
Rank	#9	Overall
	#6	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.ibm.com/products/db2

www.sqlite.org

Technical documentation

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

www.ibm.com/docs/en/db2

www.tiot.jp/riak-docs/riak/ts/latest

www.sqlite.org/docs.html

Developer

Cambridge Semantics

IBM

Open Source, formerly Basho Technologies

Dwayne Richard Hipp

Initial release

2018

1983

host version

2015

2000

Current release

2.3, January 2021

12.1, October 2016

3.0.0, September 2022

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

free version is available

Open Source

Public Domain

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

C and C++

Erlang

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X

server-less

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

restricted

yes

SQL

Support of SQL

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

yes

yes, limited

yes

SQL-92 is not fully supported

APIs and other access methods

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++
Java
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

only with Windows/Unix/Linux Version

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

with separate tools (MQ, InfoSphere)

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

fine grained access rights according to SQL-standard

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