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DBMS > Apache Impala vs. IBM Db2 Event Store vs. Quasardb vs. Splice Machine

System Properties Comparison Apache Impala vs. IBM Db2 Event Store vs. Quasardb vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonQuasardb  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed Event Store optimized for Internet of Things use casesDistributed, high-performance timeseries databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­db2-event-storequasar.aisplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ibm.com/­docs/­en/­db2-event-storedoc.quasar.ai/­mastersplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMquasardbSplice Machine
Initial release2013201720092014
Current release4.1.0, June 20222.03.14.1, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree developer edition availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++C++Java
Server operating systemsLinuxLinux infoLinux, macOS, Windows for the developer additionBSD
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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 indexesyesnoyes infowith tagsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive-active shard replicationSource-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenowith Hadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient modeyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaIBM Db2 Event StoreQuasardbSplice Machine
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