DBMS > Amazon Redshift vs. AnzoGraph DB vs. Apache Druid vs. eXtremeDB vs. RocksDB

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. Apache Druid vs. eXtremeDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Key-value store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

druid.apache.org

www.mcobject.com

rocksdb.org

Technical documentation

docs.aws.amazon.com/redshift

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

druid.apache.org/docs/latest/design

www.mcobject.com/docs/extremedb.htm

github.com/facebook/rocksdb/wiki

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

Apache Software Foundation and contributors

McObject

Facebook, Inc.

Initial release

2012

2018

2012

2001

2013

Current release

2.3, January 2021

29.0.1, April 2024

8.2, 2021

9.2.1, May 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache license v2

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

C++

Server operating systems

hosted

Linux

Linux
OS X
Unix

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

schema-less columns are supported

yes

schema-free

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.

support of XML interfaces available

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL for querying

yes

with the option: eXtremeSQL

APIs and other access methods

JDBC
ODBC

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
RESTful HTTP/JSON API

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

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

manual/auto, time-based

horizontal partitioning / sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

yes, via HDFS, S3 or other storage engines

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

not needed in graphs

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.