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DBMS > BigObject vs. Datomic vs. Heroic vs. Vertica

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

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDatomic  Xexclude from comparisonHeroic  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityTime 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 DBMS infoa hierachical model (tree) can be imposedRelational 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
Score0.13
Rank#329  Overall
#147  Relational DBMS
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitebigobject.iowww.datomic.comgithub.com/­spotify/­heroicwww.vertica.com
Technical documentationdocs.bigobject.iodocs.datomic.comspotify.github.io/­heroicvertica.com/­documentation
DeveloperBigObject, Inc.CognitectSpotifyOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201220142005
Current release1.0.7180, July 202412.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infolimited edition freeOpen 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 systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All 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 SQLSQL-like DML and DDL statementsnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
RESTful HTTP APIHQL (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
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresLuayes infoTransaction Functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoBy using transaction functionsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone 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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyes 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.yesyes inforecommended only for testing and developmentnono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
BigObjectDatomicHeroicVertica infoOpenText™ Vertica™
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