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DBMS > Apache Impala vs. Hypertable vs. Ultipa

System Properties Comparison Apache Impala vs. Hypertable vs. Ultipa

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHypertable  Xexclude from comparisonUltipa  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAn open source BigTable implementation based on distributed file systems such as HadoopHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelRelational DBMSWide column storeGraph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.19
Rank#330  Overall
#30  Graph DBMS
Websiteimpala.apache.orgwww.ultipa.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ultipa.com/­document
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHypertable Inc.Ultipa
Initial release201320092019
Current release4.1.0, June 20220.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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 statementsno
APIs and other access methodsJDBC
ODBC
C++ API
Thrift
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
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 ImpalaHypertableUltipa
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