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DBMS > Apache Impala vs. Microsoft Azure AI Search vs. Vertica

System Properties Comparison Apache Impala vs. Microsoft Azure AI Search vs. Vertica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopSearch-as-a-service for web and mobile app developmentCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsDocument storeVector DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­en-us/­services/­searchwww.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmllearn.microsoft.com/­en-us/­azure/­searchvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320152005
Current release4.1.0, June 2022V112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxhostedLinux
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBCC#
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud serviceMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infousing Azure authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaMicrosoft Azure AI SearchVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Apache ImpalaMicrosoft Azure AI SearchVertica infoOpenText™ Vertica™
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