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DBMS > GeoSpock vs. HBase vs. Netezza vs. QuestDB vs. Spark SQL

System Properties Comparison GeoSpock vs. HBase vs. Netezza vs. QuestDB vs. Spark SQL

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHBase  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleWide-column store based on Apache Hadoop and on concepts of BigTableData warehouse and analytics appliance part of IBM PureSystemsA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score30.50
Rank#26  Overall
#2  Wide column stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeospock.comhbase.apache.orgwww.ibm.com/­products/­netezzaquestdb.iospark.apache.org/­sql
Technical documentationhbase.apache.org/­book.htmlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGeoSpockApache Software Foundation infoApache top-level project, originally developed by PowersetIBMQuestDB Technology IncApache Software Foundation
Initial release2008200020142014
Current release2.0, September 20192.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoApache 2.0Open Source infoApache 2.0
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, JavascriptJavaJava (Zero-GC), C++, RustScala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux infoincluded in applianceLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-free, schema definition possibleyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyesyes
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.nononono
Secondary indexestemporal, categoricalnoyesnono
SQL infoSupport of SQLANSI SQL for query only (using Presto)noyesSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCJava API
RESTful HTTP API
Thrift
JDBC
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayesnono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUsers with fine-grained authorization conceptno
More information provided by the system vendor
GeoSpockHBaseNetezza infoAlso called PureData System for Analytics by IBMQuestDBSpark SQL
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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