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DBMS > Apache Impala vs. Splice Machine vs. SWC-DB

System Properties Comparison Apache Impala vs. Splice Machine vs. SWC-DB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonSplice Machine  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA high performance, scalable Wide Column DBMS
Primary database modelRelational DBMSRelational DBMSWide column store
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteimpala.apache.orgsplicemachine.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationimpala.apache.org/­impala-docs.htmlsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSplice MachineAlex Kashirin
Initial release201320142020
Current release4.1.0, June 20223.1, March 20210.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Proprietary protocol
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoJavano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaSplice MachineSWC-DB infoSuper Wide Column Database
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