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DBMS > Datomic vs. FileMaker vs. Vertica

System Properties Comparison Datomic vs. FileMaker vs. Vertica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFileMaker  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFileMaker is a cross-platform RDBMS that includes a GUI frontend.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 DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score49.73
Rank#20  Overall
#14  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.datomic.comwww.claris.com/­filemakerwww.vertica.com
Technical documentationdocs.datomic.comwww.claris.com/­resources/­documentationvertica.com/­documentation
DeveloperCognitectClaris infoa subsidiary of AppleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201219832005
Current release1.0.6735, June 202319.4.1, November 202112.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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++
Server operating systemsAll OS with a Java VMiOS infoclient part only
Linux
OS X
Windows
Linux
Data schemeyesyesYes, 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 dateyesyesyes
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.noyes infoA http query request can return the data in XML formatno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyes infovia pluginsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIFilemaker WebDirect
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
PHPC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsyesyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replication, warm standby infosince Version 14Multi-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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 controlnosimple rights management via user accounts and connection to external directory servicesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicFileMakerVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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DatomicFileMakerVertica infoOpenText™ Vertica™
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