DBMS > Badger vs. Geode vs. Percona Server for MongoDB vs. Riak TS

System Properties Comparison Badger vs. Geode vs. Percona Server for MongoDB vs. Riak TS

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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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Primary database model

Key-value store

Document store

Time Series DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

github.com/dgraph-io/badger

geode.apache.org

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

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

geode.apache.org/docs

docs.percona.com/percona-distribution-for-mongodb

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

Developer

DGraph Labs

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

Percona

Open Source, formerly Basho Technologies

Initial release

2017

2002

2015

Current release

1.1, February 2017

3.4.10-2.10, November 2017

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

GPL Version 2

Open Source

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

C++

Erlang

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Linux
OS X

Data scheme

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language (OQL)

yes, limited

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

proprietary protocol using JSON

HTTP API
Native Erlang Interface

Supported programming languages

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

Server-side scripts

Stored procedures

user defined functions

JavaScript

Erlang

Triggers

yes

Cache Event Listeners

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

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

via In-Memory Engine

User concepts

Access control

Access rights per client and object definable

Access rights for users and roles

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