DBMS > EventStoreDB vs. Hypertable vs. KairosDB vs. Postgres-XL vs. Valentina Server

System Properties Comparison EventStoreDB vs. Hypertable vs. KairosDB vs. Postgres-XL vs. Valentina Server

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

An open source BigTable implementation based on distributed file systems such as Hadoop

Distributed Time Series DBMS based on Cassandra or H2

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Object-relational database and reports server

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.eventstore.com

github.com/kairosdb/kairosdb

www.postgres-xl.org

www.valentina-db.net

Technical documentation

developers.eventstore.com

kairosdb.github.io

www.postgres-xl.org/documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Event Store Limited

Hypertable Inc.

Paradigma Software

Initial release

2012

2009

2013

2014

since 2012, originally named StormDB

1999

Current release

21.2, February 2021

0.9.8.11, March 2016

1.2.2, November 2018

10 R1, October 2018

5.7.5

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Windows

Linux
macOS

Linux
OS X
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.

yes

XML type, but no XML query functionality

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

C++ API
Thrift

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

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