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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Axibase vs. GridGain vs. Microsoft Azure AI Search

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Axibase vs. GridGain vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonAxibase  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure AI Search  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 networksScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationGridGain is an in-memory computing platform, built on Apache IgniteSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMSDocument store
Key-value store
Time Series DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#292  Overall
#25  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryaxibase.com/­docs/­atsd/­financewww.gridgain.comazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.htmllearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsAxibase CorporationGridGain Systems, Inc.Microsoft
Initial release20132016201320072015
Current release4.1.0, June 2022170315585GridGain 8.5.1V1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaJava, C++, .Net
Server operating systemsLinuxLinuxLinuxLinux
OS X
Solaris
Windows
hosted
Data schemeyesSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateyesoptionalyes infoshort, integer, long, float, double, decimal, stringyesyes
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.noyesnoyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
LDAPJDBC
Proprietary protocol (Network API)
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsGo
Java
PHP
Python
R
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesyes (compute grid and cache interceptors can be used instead)no
Triggersnoyesyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationyes (replicated cache)yes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationSecurity Hooks for custom implementationsyes infousing Azure authentication

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More resources
Apache ImpalaAtos Standard Common RepositoryAxibaseGridGainMicrosoft Azure AI Search
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