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DBMS > Apache Impala vs. Atos Standard Common Repository vs. HEAVY.AI

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationimpala.apache.org/­impala-docs.htmldocs.heavy.ai
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsHEAVY.AI, Inc.
Initial release201320162016
Current release4.1.0, June 202217035.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++ and CUDA
Server operating systemsLinuxLinuxLinux
Data schemeyesSchema and schema-less with LDAP viewsyes
Typing infopredefined data types such as float or dateyesoptionalyes
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
LDAPJDBC
ODBC
Thrift
Vega
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsAll languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaAtos Standard Common RepositoryHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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