DBMS > AnzoGraph DB vs. Realm vs. SingleStore vs. STSdb

System Properties Comparison AnzoGraph DB vs. Realm vs. SingleStore vs. STSdb

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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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	5.91
Rank	#61	Overall
	#34	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

cambridgesemantics.com/anzograph

realm.io

www.singlestore.com

github.com/STSSoft/STSdb4

Technical documentation

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

realm.io/docs

docs.singlestore.com

Developer

Cambridge Semantics

Realm, acquired by MongoDB in May 2019

SingleStore Inc.

STS Soft SC

Initial release

2018

2014

2013

2011

Current release

2.3, January 2021

8.5, January 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

commercial

free developer edition available

Open Source

GPLv2, 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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++, Go

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

Linux

64 bit version required

Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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 foreign keys

APIs and other access methods

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

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

.NET Client API

Supported programming languages

C++
Java
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

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

C#
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

hash partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Source-replica replication

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

none

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

Foreign keys

Referential integrity

not needed in graphs

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

In-Memory realm

yes

User concepts

Access control

Access rights for users and roles

yes

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

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Recent citations in the news

AnzoGraph review: 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

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

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

How Knowledge Graphs Automate Data Preparation
15 July 2020, Database Trends and Applications

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Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

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12 September 2017, Solutions Review

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SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks and Files

SingleStore Accelerates Go-to-Market Strategy with AWS
5 March 2024, Business Wire

New AI features for developers in SingleStoreDB
29 January 2024, InfoWorld

SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps
3 January 2024, Acceleration Economy

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