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DBMS > Cassandra vs. Impala vs. RDF4J vs. Sphinx

System Properties Comparison Cassandra vs. Impala vs. RDF4J vs. Sphinx

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Editorial information provided by DB-Engines
NameCassandra  Xexclude from comparisonImpala  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionWide-column store based on ideas of BigTable and DynamoDB infoOptimized for write accessAnalytic DBMS for HadoopRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelWide column storeRelational DBMSRDF storeSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score120.95
Rank#11  Overall
#1  Wide column stores
Score15.70
Rank#36  Overall
#22  Relational DBMS
Score0.42
Rank#219  Overall
#10  RDF stores
Score6.69
Rank#51  Overall
#5  Search engines
Websitecassandra.apache.orgwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlrdf4j.orgsphinxsearch.com
Technical documentationcassandra.apache.org/­doc/­latestwww.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmldocs.rdf4j.orgsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top level project, originally developped by FacebookClouderaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sphinx Technologies Inc.
Initial release2008201320042001
Current release3.11.6, February 20203.3.0, August 20193.1.1, October 2018
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC++
Server operating systemsBSD
Linux
OS X
Windows
LinuxLinux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesrestricted infoonly equality queries, not always the best performing solutionyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like SELECT, DML and DDL statements (CQL)SQL-like DML and DDL statementsnoSQL-like query language (SphinxQL)
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Proprietary protocol
Supported programming languagesC#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript infoNode.js
Perl
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCJava
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possibleselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnono
More information provided by the system vendor
CassandraImpalaRDF4J infoformerly known as SesameSphinx
Specific characteristicsApache Cassandra is the leading NoSQL, distributed database management system, well...
» more
Competitive advantagesNo single point of failure ensures 100% availability . Operational simplicity for...
» more
Typical application scenariosInternet of Things (IOT), fraud detection applications, recommendation engines, product...
» more
Key customersApple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more
Market metricsCassandra is used by 40% of the Fortune 100.
» more
Licensing and pricing modelsApache license  Pricing for commercial distributions provided by DataStax and available...
» more

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More resources
CassandraImpalaRDF4J infoformerly known as SesameSphinx
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