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DBMS > Hive vs. IBM Db2 Event Store vs. Spark SQL vs. SwayDB vs. TimescaleDB

System Properties Comparison Hive vs. IBM Db2 Event Store vs. Spark SQL vs. SwayDB vs. TimescaleDB

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed Event Store optimized for Internet of Things use casesSpark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Relational DBMSKey-value storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitehive.apache.orgwww.ibm.com/­products/­db2-event-storespark.apache.org/­sqlswaydb.simer.auwww.timescale.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperApache Software Foundation infoinitially developed by FacebookIBMApache Software FoundationSimer PlahaTimescale
Initial release20122017201420182017
Current release3.1.3, April 20222.03.5.0 ( 2.13), September 20232.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree developer edition availableOpen Source infoApache 2.0Open Source infoGNU Affero GPL V3.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++ScalaScalaC
Server operating systemsAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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.nononoyes
Secondary indexesyesnononoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
Python
R
Scala
Java
Kotlin
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive-active shard replicationnonenoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
HiveIBM Db2 Event StoreSpark SQLSwayDBTimescaleDB
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