DBMS > Apache Druid vs. Hypertable vs. Postgres-XL vs. Trafodion vs. Transbase

System Properties Comparison Apache Druid vs. Hypertable vs. Postgres-XL vs. Trafodion vs. Transbase

Editorial information provided by DB-Engines

Name

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

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

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

Transactional SQL-on-Hadoop DBMS

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

Primary database model

Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

druid.apache.org

www.postgres-xl.org

trafodion.apache.org

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

Technical documentation

druid.apache.org/docs/latest/design

www.postgres-xl.org/documentation

trafodion.apache.org/documentation.html

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

Developer

Apache Software Foundation and contributors

Hypertable Inc.

Apache Software Foundation, originally developed by HP

Transaction Software GmbH

Initial release

2012

2009

2014

since 2012, originally named StormDB

2014

1987

Current release

29.0.1, April 2024

0.9.8.11, March 2016

10 R1, October 2018

2.3.0, February 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GNU version 3. Commercial license available

Open Source

Mozilla public license

Open Source

Apache 2.0

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++

C++, Java

C and C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL for querying

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

C++ API
Thrift

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

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

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor on file system level

yes, via HBase

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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