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DBMS > Amazon CloudSearch vs. Netezza vs. QuestDB vs. RDFox vs. Sphinx

System Properties Comparison Amazon CloudSearch vs. Netezza vs. QuestDB vs. RDFox vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuestDB  Xexclude from comparisonRDFox  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudData warehouse and analytics appliance part of IBM PureSystemsA high performance open source SQL database for time series dataHigh performance knowledge graph and semantic reasoning engineOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineRelational DBMSTime Series DBMSGraph DBMS
RDF store
Search engine
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­cloudsearchwww.ibm.com/­products/­netezzaquestdb.iowww.oxfordsemantic.techsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­cloudsearchquestdb.io/­docsdocs.oxfordsemantic.techsphinxsearch.com/­docs
DeveloperAmazonIBMQuestDB Technology IncOxford Semantic TechnologiesSphinx Technologies Inc.
Initial release20122000201420172001
Current release6.0, Septermber 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava (Zero-GC), C++, RustC++C++
Server operating systemshostedLinux infoincluded in applianceLinux
macOS
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocolyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.no
Secondary indexesyes infoall search fields are automatically indexedyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesSQL with time-series extensionsnoSQL-like query language (SphinxQL)
APIs and other access methodsHTTP APIJDBC
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
RESTful HTTP API
SPARQL 1.1
Proprietary protocol
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C
Java
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-replica replicationSource-replica replication with eventual consistencyreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID for single-table writesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yes infothrough memory mapped filesyes
User concepts infoAccess controlauthentication via encrypted signaturesUsers with fine-grained authorization conceptRoles, resources, and access typesno
More information provided by the system vendor
Amazon CloudSearchNetezza infoAlso called PureData System for Analytics by IBMQuestDBRDFoxSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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