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DBMS > Apache Impala vs. Apache Pinot vs. Hypertable

System Properties Comparison Apache Impala vs. Apache Pinot vs. Hypertable

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Pinot  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelRelational DBMSRelational DBMSWide column store
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
Score0.40
Rank#270  Overall
#125  Relational DBMS
Websiteimpala.apache.orgpinot.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.pinot.apache.org
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation and contributorsHypertable Inc.
Initial release201320152009
Current release4.1.0, June 20221.0.0, September 20230.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license available
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 systemsLinuxAll OS with a Java JDK11 or higherLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.no
Secondary indexesyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsJDBC
ODBC
JDBCC++ API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
Apache ImpalaApache PinotHypertable
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