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DBMS > Datomic vs. Microsoft Azure Synapse Analytics vs. Realm vs. Sphinx vs. Vertica

System Properties Comparison Datomic vs. Microsoft Azure Synapse Analytics vs. Realm vs. Sphinx vs. Vertica

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRealm  Xexclude from comparisonSphinx  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen source search engine for searching in data from different sources, e.g. relational databasesCloud 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 DBMSRelational DBMSDocument storeSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial 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
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­synapse-analyticsrealm.iosphinxsearch.comwww.vertica.com
Technical documentationdocs.datomic.comdocs.microsoft.com/­azure/­synapse-analyticsrealm.io/­docssphinxsearch.com/­docsvertica.com/­documentation
DeveloperCognitectMicrosoftRealm, acquired by MongoDB in May 2019Sphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122016201420012005
Current release1.0.6735, June 20233.5.1, February 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen SourceOpen Source infoGPL version 2, commercial licence availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++C++C++
Server operating systemsAll OS with a Java VMhostedAndroid
Backend: server-less
iOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesYes, 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 dateyesyesyesnoyes
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 indexesyesyesyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesnoSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
C#
Java
PHP
.Net
Java infowith Android only
Objective-C
React Native
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction FunctionsTransact SQLno inforuns within the applications so server-side scripts are unnecessarynoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsnoyes infoChange Listenersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding, horizontal partitioningnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesnonenoneMulti-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 methodsnonononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
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 infoThe original contents of fields are not stored in the Sphinx index.yes
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 developmentyes infoIn-Memory realmno
User concepts infoAccess controlnoyesyesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRealmSphinxVertica 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...
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More resources
DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRealmSphinxVertica infoOpenText™ Vertica™
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