DBMS > Datastax Enterprise vs. EXASOL vs. Kdb vs. Snowflake vs. SWC-DB

System Properties Comparison Datastax Enterprise vs. EXASOL vs. Kdb vs. Snowflake vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

High performance Time Series DBMS

Cloud-based data warehousing service for structured and semi-structured data

A high performance, scalable Wide Column DBMS

Primary database model

Wide column store

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Wide column store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Relational DBMS

Time Series DBMS

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

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.datastax.com/products/datastax-enterprise

www.exasol.com

kx.com

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.datastax.com

www.exasol.com/resources

code.kx.com

docs.snowflake.net/manuals/index.html

Developer

DataStax

Exasol

Kx Systems, a division of First Derivatives plc

Snowflake Computing Inc.

Alex Kashirin

Initial release

2011

2000

kdb was released 2000, kdb+ in 2003

2014

2020

Current release

6.8, April 2020

3.6, May 2018

0.5, April 2021

License

Commercial or Open Source

commercial

free 32-bit version

commercial

Open Source

GPL V3

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

C++

Server operating systems

Linux
OS X

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

table attribute 'grouped'

SQL

Support of SQL

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

yes

SQL-like query language (q)

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

.Net
JDBC
ODBC
WebSocket

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

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

Java
Lua
Python
R

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

with views

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

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 can be defined per object

Access rights for users, groups and roles according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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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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kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

Annual subscription
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upon request
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