DBMS > Blueflood vs. Cassandra vs. GeoSpock vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison Blueflood vs. Cassandra vs. GeoSpock vs. SAP SQL Anywhere vs. Sphinx

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Spatial and temporal data processing engine for extreme data scale

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Time Series DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

blueflood.io

cassandra.apache.org

geospock.com

www.sap.com/products/technology-platform/sql-anywhere.html

sphinxsearch.com

Technical documentation

github.com/rax-maas/blueflood/wiki

cassandra.apache.org/doc/latest

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

Rackspace

Apache Software Foundation

Apache top level project, originally developped by Facebook

GeoSpock

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

2013

2008

1992

2001

Current release

4.1.3, July 2023

2.0, September 2019

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

Open Source

GPL version 2, commercial licence available

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Java, Javascript

C++

Server operating systems

Linux
OS X

BSD
Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

predefined scheme

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

restricted

only equality queries, not always the best performing solution

temporal, categorical

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

ANSI SQL for query only (using Presto)

yes

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP REST

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

no "single point of failure"

Automatic sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

can be individually decided for 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

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

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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