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DBMS > Apache Impala vs. EXASOL vs. Google BigQuery vs. Microsoft Azure AI Search vs. Microsoft SQL Server

System Properties Comparison Apache Impala vs. EXASOL vs. Google BigQuery vs. Microsoft Azure AI Search vs. Microsoft SQL Server

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Large scale data warehouse service with append-only tablesSearch-as-a-service for web and mobile app developmentMicrosofts flagship relational DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeVector DBMSDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score824.29
Rank#3  Overall
#3  Relational DBMS
Websiteimpala.apache.orgwww.exasol.comcloud.google.com/­bigqueryazure.microsoft.com/­en-us/­services/­searchwww.microsoft.com/­en-us/­sql-server
Technical documentationimpala.apache.org/­impala-docs.htmlwww.exasol.com/­resourcescloud.google.com/­bigquery/­docslearn.microsoft.com/­en-us/­azure/­searchlearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaExasolGoogleMicrosoftMicrosoft
Initial release20132000201020151989
Current release4.1.0, June 2022V1SQL Server 2022, November 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++C++
Server operating systemsLinuxhostedhostedLinux
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesnoyes
APIs and other access methodsJDBC
ODBC
.Net
JDBC
ODBC
WebSocket
RESTful HTTP/JSON APIRESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesAll languages supporting JDBC/ODBCJava
Lua
Python
R
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
Java
JavaScript
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsuser defined functions infoin JavaScriptnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud servicetables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud serviceyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno infoSince BigQuery is designed for querying datanoACID
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.noyesnonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)yes infousing Azure authenticationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaEXASOLGoogle BigQueryMicrosoft Azure AI SearchMicrosoft SQL Server
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