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DBMS > Datomic vs. EventStoreDB vs. FoundationDB vs. Vertica

System Properties Comparison Datomic vs. EventStoreDB vs. FoundationDB vs. Vertica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEventStoreDB  Xexclude from comparisonFoundationDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityIndustrial-strength, open-source database solution built from the ground up for event sourcing.Ordered key-value store. Core features are complimented by layers.Cloud 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 DBMSEvent StoreDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.19
Rank#173  Overall
#1  Event Stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.datomic.comwww.eventstore.comgithub.com/­apple/­foundationdbwww.vertica.com
Technical documentationdocs.datomic.comdevelopers.eventstore.comapple.github.io/­foundationdbvertica.com/­documentation
DeveloperCognitectEvent Store LimitedFoundationDBOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201220132005
Current release1.0.6735, June 202321.2, February 20216.2.28, November 202012.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen SourceOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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, ClojureC++C++
Server operating systemsAll OS with a Java VMLinux
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-free infosome layers support schemasYes, 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 typingyes
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.nono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnosupported in specific SQL layer onlyFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsin SQL-layer onlyyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integritynoin SQL-layer onlyyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentno
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicEventStoreDBFoundationDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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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DatomicEventStoreDBFoundationDBVertica infoOpenText™ Vertica™
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