DBMS > Amazon Redshift vs. Datastax Enterprise vs. Faircom DB vs. Stardog vs. VoltDB

System Properties Comparison Amazon Redshift vs. Datastax Enterprise vs. Faircom DB vs. Stardog vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Wide column store

Key-value store
Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

aws.amazon.com/redshift

www.datastax.com/products/datastax-enterprise

www.faircom.com/products/faircom-db

www.stardog.com

www.voltdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.datastax.com

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.stardog.com

docs.voltdb.com

Developer

Amazon (based on PostgreSQL)

DataStax

FairCom Corporation

Stardog-Union

VoltDB Inc.

Initial release

2012

2011

1979

2010

Current release

6.8, April 2020

V12, November 2020

7.3.0, May 2020

11.3, April 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

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

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.

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Implementation language

Java

ANSI C, C++

Java

Java, C++

Server operating systems

hosted

Linux
OS X

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

schema free, schema optional, schema required, partial schema,

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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.

Import/export of XML data possible

Secondary indexes

restricted

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements (CQL); Spark SQL

yes, ANSI SQL with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

.Net, JavaScript, C/C++

user defined functions and aggregates, HTTP Server extensions in Java

Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

tunable from ACID to Eventually Consistent

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

Snapshots and command logging

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 can be defined per object

Fine grained access rights according to SQL-standard with additional protections for files

Access rights for users and roles

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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