DBMS > Datastax Enterprise vs. Kdb vs. RocksDB vs. Sphinx

System Properties Comparison Datastax Enterprise vs. Kdb vs. RocksDB vs. Sphinx

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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 Time Series DBMS

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Wide column store

Time Series DBMS
Vector DBMS

Key-value store

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Relational DBMS

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

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

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

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

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.datastax.com/products/datastax-enterprise

kx.com

rocksdb.org

sphinxsearch.com

Technical documentation

docs.datastax.com

code.kx.com

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

DataStax

Kx Systems, a division of First Derivatives plc

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

2011

2000

kdb was released 2000, kdb+ in 2003

2013

2001

Current release

6.8, April 2020

3.6, May 2018

9.2.1, May 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

BSD

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X

Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

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

Secondary indexes

yes

table attribute 'grouped'

yes

full-text index on all search fields

SQL

Support of SQL

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

SQL-like query language (q)

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

C++ API
Java API

Proprietary protocol

Supported programming languages

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

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

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

rights management via user accounts

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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