DBMS > Badger vs. Kinetica vs. Newts vs. Prometheus vs. Trafodion

System Properties Comparison Badger vs. Kinetica vs. Newts vs. Prometheus vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Fully vectorized database across both GPUs and CPUs

Time Series DBMS based on Cassandra

Open-source Time Series DBMS and monitoring system

Transactional SQL-on-Hadoop DBMS

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	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.kinetica.com

opennms.github.io/newts

prometheus.io

trafodion.apache.org

Technical documentation

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

docs.kinetica.com

github.com/OpenNMS/newts/wiki

prometheus.io/docs

trafodion.apache.org/documentation.html

Developer

DGraph Labs

Kinetica

OpenNMS Group

Apache Software Foundation, originally developed by HP

Initial release

2017

2012

2014

2015

2014

Current release

7.1, August 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

C, C++

Java

C++, Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Java

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

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

Source-replica replication

selectable replication factor

based on Cassandra

yes

by Federation

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency

Foreign keys

Referential integrity

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

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 and roles on table level

fine grained access rights according to SQL-standard

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