DBMS > Badger vs. IBM Cloudant vs. Kinetica vs. Newts vs. Prometheus

System Properties Comparison Badger vs. IBM Cloudant vs. Kinetica vs. Newts vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

Fully vectorized database across both GPUs and CPUs

Time Series DBMS based on Cassandra

Open-source Time Series DBMS and monitoring system

Primary database model

Secondary database models

Spatial DBMS
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	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Website

github.com/dgraph-io/badger

www.ibm.com/products/cloudant

www.kinetica.com

opennms.github.io/newts

prometheus.io

Technical documentation

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

cloud.ibm.com/docs/Cloudant

docs.kinetica.com

github.com/OpenNMS/newts/wiki

prometheus.io/docs

Developer

DGraph Labs

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Kinetica

OpenNMS Group

Initial release

2017

2010

2012

2014

2015

Current release

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Erlang

C, C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Linux

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

RESTful HTTP/JSON API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

Java

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

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor

based on Cassandra

yes

by Federation

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles on table level

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