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DBMS > Netezza vs. Oracle Berkeley DB vs. QuestDB vs. Sphinx vs. SQream DB

System Properties Comparison Netezza vs. Oracle Berkeley DB vs. QuestDB vs. Sphinx vs. SQream DB

Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsWidely used in-process key-value storeA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databasesa GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMSSearch engineRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlquestdb.iosphinxsearch.comsqream.com
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlquestdb.io/­docssphinxsearch.com/­docsdocs.sqream.com
DeveloperIBMOracle infooriginally developed by Sleepycat, which was acquired by OracleQuestDB Technology IncSphinx Technologies Inc.SQream Technologies
Initial release20001994201420012017
Current release18.1.40, May 20203.5.1, February 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)Java (Zero-GC), C++, RustC++C++, CUDA, Haskell, Java, Scala
Server operating systemsLinux infoincluded in applianceAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyes infoschema-free via InfluxDB Line Protocolyesyes
Typing infopredefined data types such as float or dateyesnoyesnoyes, ANSI Standard SQL Types
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.yes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyesyes infoSQL interfaced based on SQLite is availableSQL with time-series extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol.Net
JDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnononouser defined functions in Python
Triggersnoyes infoonly for the SQL APInonono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationSource-replica replication with eventual consistencynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID for single-table writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infothrough memory mapped files
User concepts infoAccess controlUsers with fine-grained authorization conceptnono
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMOracle Berkeley DBQuestDBSphinxSQream DB
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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