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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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 durabilityA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen 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 DBMSSearch engineRelational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Spatial DBMS
Vector 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
Score135.35
Rank#7  Overall
#1  Search engines
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.datomic.comwww.elastic.co/­elasticsearchazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comwww.vertica.com
Technical documentationdocs.datomic.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docsvertica.com/­documentation
DeveloperCognitectElasticMicrosoftSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122010201620012005
Current release1.0.6735, June 20238.6, January 20233.5.1, February 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoElastic LicensecommercialOpen Source infoGPL version 2, commercial licence availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesnono 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, ClojureJavaC++C++C++
Server operating systemsAll OS with a Java VMAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesYes, 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 indexesyesyes infoAll search fields are automatically indexedyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languageyesSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
ADO.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
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Java
PHP
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 FunctionsyesTransact SQLnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsyes infoby using the 'percolation' featurenonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding, horizontal partitioningSharding 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 peersyesyesnoneMulti-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 methodsnoES-Hadoop Connectornonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 developmentMemcached and Redis integrationno
User concepts infoAccess controlnoyesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxVertica 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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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DatomicElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxVertica infoOpenText™ Vertica™
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