DBMS > Badger vs. Prometheus vs. Riak TS vs. TimesTen

System Properties Comparison Badger vs. Prometheus vs. Riak TS vs. TimesTen

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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.

Open-source Time Series DBMS and monitoring system

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

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

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

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

github.com/dgraph-io/badger

prometheus.io

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

prometheus.io/docs

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

docs.oracle.com/database/timesten-18.1

Developer

DGraph Labs

Open Source, formerly Basho Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

2015

1998

Current release

3.0.0, September 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

commercial

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

Erlang

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Import of XML data possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Erlang

PL/SQL

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by Federation

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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