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DBMS > EsgynDB vs. FoundationDB vs. Microsoft Azure AI Search vs. PostgreSQL vs. Vertica

System Properties Comparison EsgynDB vs. FoundationDB vs. Microsoft Azure AI Search vs. PostgreSQL vs. Vertica

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPostgreSQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOrdered key-value store. Core features are complimented by layers.Search-as-a-service for web and mobile app developmentWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLCloud 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 DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Search engineRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS infoColumn oriented
Secondary database modelsVector DBMSDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.esgyn.cngithub.com/­apple/­foundationdbazure.microsoft.com/­en-us/­services/­searchwww.postgresql.orgwww.vertica.com
Technical documentationapple.github.io/­foundationdblearn.microsoft.com/­en-us/­azure/­searchwww.postgresql.org/­docsvertica.com/­documentation
DeveloperEsgynFoundationDBMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201320151989 info1989: Postgres, 1996: PostgreSQL2005
Current release6.2.28, November 2020V116.3, May 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoBSDcommercial 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

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Implementation languageC++, JavaC++CC++
Server operating systemsLinuxLinux
OS X
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
Data schemeyesschema-free infosome layers support schemasyesyesYes, 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 dateyesno infosome layers support typingyesyesyes
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 infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyessupported in specific SQL layer onlynoyes infostandard with numerous extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful 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 languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
Java
JavaScript
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresin SQL-layer onlynouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesyes infoImplicit feature of the cloud serviceSource-replica replication infoother methods possible by using 3rd party extensionsMulti-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 methodsyesnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesin SQL-layer onlynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes 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
EsgynDBFoundationDBMicrosoft Azure AI SearchPostgreSQLVertica 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
EsgynDBFoundationDBMicrosoft Azure AI SearchPostgreSQLVertica infoOpenText™ Vertica™
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