DBMS > Apache Phoenix vs. EventStoreDB vs. Machbase Neo vs. Postgres-XL vs. Transbase

System Properties Comparison Apache Phoenix vs. EventStoreDB vs. Machbase Neo vs. Postgres-XL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

TimeSeries DBMS for AIoT and BigData

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.transaction.de/en/products/transbase.html

Technical documentation

phoenix.apache.org

developers.eventstore.com

machbase.com/dbms

www.postgres-xl.org/documentation

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Event Store Limited

Machbase

Transaction Software GmbH

Initial release

2014

2012

2013

2014

since 2012, originally named StormDB

1987

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

21.2, February 2021

V8.0, August 2023

10 R1, October 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

free test version available

Open Source

Mozilla public license

commercial

free development license

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

Java

C and C++

Server operating systems

Linux
Unix
Windows

Linux
Windows

Linux
macOS
Windows

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

SQL

Support of SQL

yes

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC

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

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

yes

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

volatile and lookup table

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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