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DBMS > Apache Impala vs. Hypertable vs. Microsoft Azure Data Explorer vs. openGauss

System Properties Comparison Apache Impala vs. Hypertable vs. Microsoft Azure Data Explorer vs. openGauss

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonopenGauss  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 HadoopFully managed big data interactive analytics platformAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei
Primary database modelRelational DBMSWide column storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument storeDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.08
Rank#183  Overall
#84  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­data-explorergitee.com/­opengauss
opengauss.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHypertable Inc.MicrosoftHuawei and openGauss community
Initial release2013200920192019
Current release4.1.0, June 20220.9.8.11, March 2016cloud service with continuous releases3.0, March 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU version 3. Commercial license availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C, C++, Java
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 indexesyesrestricted infoonly exact value or prefix value scansall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subsetANSI SQL 2011
APIs and other access methodsJDBC
ODBC
C++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoYes, possible languages: KQL, Python, Ryes
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by range, list and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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Apache ImpalaHypertableMicrosoft Azure Data ExploreropenGauss
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