DBMS > etcd vs. IBM Db2 warehouse vs. Kinetica vs. Machbase Neo

System Properties Comparison etcd vs. IBM Db2 warehouse vs. Kinetica vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Cloud-based data warehousing service

Fully vectorized database across both GPUs and CPUs

TimeSeries DBMS for AIoT and BigData

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.ibm.com/products/db2/warehouse

www.kinetica.com

machbase.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.kinetica.com

machbase.com/dbms

Developer

IBM

Kinetica

Machbase

Initial release

2014

2012

2013

Current release

3.4, August 2019

7.1, August 2021

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

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

C, C++

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

gRPC
JSON over HTTP

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

PL/SQL, SQL PL

user defined functions

Triggers

yes, watching key changes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

simple password-based access control

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