DBMS > Apache Impala vs. EDB Postgres vs. Postgres-XL vs. VoltDB

System Properties Comparison Apache Impala vs. EDB Postgres vs. Postgres-XL vs. VoltDB

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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.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational 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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

www.enterprisedb.com/docs

www.postgres-xl.org/documentation

docs.voltdb.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

EnterpriseDB

VoltDB Inc.

Initial release

2013

2005

2014

since 2012, originally named StormDB

2010

Current release

4.1.0, June 2022

14, December 2021

10 R1, October 2018

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

BSD for PostgreSQL-components

Open Source

Mozilla public license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

Linux

Linux
Windows

Linux
macOS

Linux
OS X

for development

Data scheme

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

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

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

yes

distributed, parallel query execution

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

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.

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

MVCC

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

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

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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Nutanix partners with EDB to fit database service for AI – Blocks and Files
21 May 2024, Blocks & Files

Nutanix and EDB Partner to Deliver a Modern Data Platform
21 May 2024, Business Wire

EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack
22 April 2024, Datanami

EDB Is Developing Its Flagship Database Into A Comprehensive Platform For Analytics, AI
27 February 2024, CRN

EDB Introduces Advanced Tools and Extensions in Postgres 16 Portfolio Release
9 November 2023, GlobeNewswire

provided by Google News

Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News

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