DBMS > Badger vs. Geode vs. Microsoft Azure Cosmos DB vs. STSdb vs. TerminusDB

System Properties Comparison Badger vs. Geode vs. Microsoft Azure Cosmos DB vs. STSdb vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Globally distributed, horizontally scalable, multi-model database service

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	1.51
Rank	#147	Overall
	#25	Key-value stores

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

github.com/dgraph-io/badger

geode.apache.org

azure.microsoft.com/services/cosmos-db

github.com/STSSoft/STSdb4

terminusdb.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

geode.apache.org/docs

learn.microsoft.com/azure/cosmos-db

terminusdb.github.io/terminusdb/#

Developer

DGraph Labs

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

STS Soft SC

DataChemist Ltd.

Initial release

2017

2002

2014

2011

2018

Current release

1.1, February 2017

4.0.8, September 2015

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

GPLv2, commercial license available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Prolog, Rust

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

primitive types and user defined types (classes)

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language (OQL)

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

.NET Client API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

Triggers

yes

Cache Event Listeners

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

Implicit feature of the cloud service

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 per client and object definable

Access rights can be defined down to the item level

Role-based access control

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