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DBMS > Datomic vs. EXASOL vs. Heroic vs. Vertica

System Properties Comparison Datomic vs. EXASOL vs. Heroic vs. Vertica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEXASOL  Xexclude from comparisonHeroic  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchCloud 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 DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.datomic.comwww.exasol.comgithub.com/­spotify/­heroicwww.vertica.com
Technical documentationdocs.datomic.comwww.exasol.com/­resourcesspotify.github.io/­heroicvertica.com/­documentation
DeveloperCognitectExasolSpotifyOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012200020142005
Current release1.0.7075, December 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen 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, ClojureJavaC++
Server operating systemsAll OS with a Java VMLinux
Data schemeyesyesschema-freeYes, 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 dateyesyesyesyes
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 indexesyesyesyes infovia ElasticsearchNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP API.Net
JDBC
ODBC
WebSocket
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
Java
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardinghorizontal 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 methodsnoyes infoHadoop integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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
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 developmentyesnono
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicEXASOLHeroicVertica 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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DatomicEXASOLHeroicVertica infoOpenText™ Vertica™
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