DBMS > AnzoGraph DB vs. PostgreSQL vs. SingleStore vs. Warp 10

System Properties Comparison AnzoGraph DB vs. PostgreSQL vs. SingleStore vs. Warp 10

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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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Graph DBMS
RDF store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

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

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Score	3.69
Rank	#70	Overall
	#37	Relational DBMS

Score	0.15
Rank	#331	Overall
	#30	Time Series DBMS

Website

cambridgesemantics.com/anzograph

www.postgresql.org

www.singlestore.com

www.warp10.io

Technical documentation

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

www.postgresql.org/docs

docs.singlestore.com

www.warp10.io/content/02_Getting_started

Developer

Cambridge Semantics

PostgreSQL Global Development Group

www.postgresql.org/developer

SingleStore Inc.

SenX

Initial release

2018

1989

1989: Postgres, 1996: PostgreSQL

2013

2015

Current release

2.3, January 2021

16.4, August 2024

8.5, January 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

BSD

commercial

free developer edition available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++, Go

Java

Server operating systems

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux

64 bit version required

Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

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

yes

standard with numerous extensions

yes

but no triggers and foreign keys

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

C++
Java
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

hash partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

stores two copies of each physical data partition on two separate nodes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

based on HBase

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)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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