DBMS > Apache Impala vs. EDB Postgres vs. eXtremeDB vs. OpenTSDB

System Properties Comparison Apache Impala vs. EDB Postgres vs. eXtremeDB vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Natively in-memory DBMS with options for persistency, high-availability and clustering

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

www.enterprisedb.com/docs

www.mcobject.com/docs/extremedb.htm

opentsdb.net/docs/build/html/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

EnterpriseDB

McObject

currently maintained by Yahoo and other contributors

Initial release

2013

2005

2001

2011

Current release

4.1.0, June 2022

14, December 2021

8.2, 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

BSD for PostgreSQL-components

commercial

Open Source

LGPL

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 and C++

Java

Server operating systems

Linux

Linux
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

specific XML-type available, but no XML query functionality.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

yes

with the option: eXtremeSQL

APIs and other access methods

JDBC
ODBC

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

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Java
Lua
Python
Scala

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

horizontal partitioning / sharding

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

based on HBase

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

yes, multi-version concurrency control (MVCC)

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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Recent citations in the news

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