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DBMS > Datomic vs. Microsoft Azure AI Search vs. Postgres-XL vs. Vertica

System Properties Comparison Datomic vs. Microsoft Azure AI Search vs. Postgres-XL vs. Vertica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPostgres-XL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySearch-as-a-service for web and mobile app developmentBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresCloud 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 DBMSRelational DBMS infoColumn oriented
Secondary database modelsVector DBMSDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.datomic.comazure.microsoft.com/­en-us/­services/­searchwww.postgres-xl.orgwww.vertica.com
Technical documentationdocs.datomic.comlearn.microsoft.com/­en-us/­azure/­searchwww.postgres-xl.org/­documentationvertica.com/­documentation
DeveloperCognitectMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220152014 infosince 2012, originally named StormDB2005
Current release1.0.6735, June 2023V110 R1, October 201812.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoMozilla public licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono 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 languageJava, ClojureCC++
Server operating systemsAll OS with a Java VMhostedLinux
macOS
Linux
Data schemeyesyesyesYes, 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 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.nonoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoyes infodistributed, parallel query executionFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
C#
Java
JavaScript
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud servicehorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes 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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnonono
User concepts infoAccess controlnoyes infousing Azure authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicMicrosoft Azure AI SearchPostgres-XLVertica 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...
» more
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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DatomicMicrosoft Azure AI SearchPostgres-XLVertica infoOpenText™ Vertica™
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