DBMS > Apache Impala vs. Blazegraph vs. eXtremeDB vs. MySQL vs. PostGIS

System Properties Comparison Apache Impala vs. Blazegraph vs. eXtremeDB vs. MySQL vs. PostGIS

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Analytic DBMS for Hadoop

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

Widely used open source RDBMS

Spatial extension of PostgreSQL

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

wiki.blazegraph.com

www.mcobject.com/docs/extremedb.htm

dev.mysql.com/doc

postgis.net/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Blazegraph

McObject

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2013

2006

2001

1995

2005

Current release

4.1.0, June 2022

2.1.5, March 2019

8.2, 2021

8.3.0, January 2024

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

extended commercial license available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C and C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SPARQL is used as query language

yes

with the option: eXtremeSQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

user defined functions

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

table locks or row locks depending on storage engine

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Users with fine-grained authorization concept

no user groups or roles

yes

based on PostgreSQL

More information provided by the system vendor

Specific characteristics

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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

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