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DBMS > Apache Impala vs. GeoSpock vs. Spark SQL vs. STSdb

System Properties Comparison Apache Impala vs. GeoSpock vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGeoSpock  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopSpatial and temporal data processing engine for extreme data scaleSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Websiteimpala.apache.orggeospock.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeoSpockApache Software FoundationSTS Soft SC
Initial release201320142011
Current release4.1.0, June 20222.0, September 20193.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, JavascriptScalaC#
Server operating systemsLinuxhostedLinux
OS X
Windows
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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.nonono
Secondary indexesyestemporal, categoricalnono
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for query only (using Presto)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
JDBCJDBC
ODBC
.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBCJava
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per tablenono

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More resources
Apache ImpalaGeoSpockSpark SQLSTSdb
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