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DBMS > Apache Impala vs. EsgynDB vs. Microsoft Azure AI Search vs. Warp 10

System Properties Comparison Apache Impala vs. EsgynDB vs. Microsoft Azure AI Search vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSearch-as-a-service for web and mobile app developmentTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteimpala.apache.orgwww.esgyn.cnazure.microsoft.com/­en-us/­services/­searchwww.warp10.io
Technical documentationimpala.apache.org/­impala-docs.htmllearn.microsoft.com/­en-us/­azure/­searchwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynMicrosoftSenX
Initial release2013201520152015
Current release4.1.0, June 2022V1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaJava
Server operating systemsLinuxLinuxhostedLinux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnono
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
RESTful HTTP APIHTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetC#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresnoyes infoWarpScript
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersyes infoImplicit feature of the cloud serviceselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyes infousing Azure authenticationMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache ImpalaEsgynDBMicrosoft Azure AI SearchWarp 10
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