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DBMS > BoltDB vs. Datomic vs. EXASOL vs. Vertica

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

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDatomic  Xexclude from comparisonEXASOL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Datomic 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.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 modelKey-value storeRelational 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
Score0.80
Rank#215  Overall
#31  Key-value stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.datomic.comwww.exasol.comwww.vertica.com
Technical documentationdocs.datomic.comwww.exasol.com/­resourcesvertica.com/­documentation
DeveloperCognitectExasolOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201220002005
Current release1.0.7075, December 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMIT Licensecommercial infolimited edition freecommercialcommercial 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 languageGoJava, ClojureC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
Data schemeschema-freeyesyesYes, 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 datenoyesyesyes
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 indexesnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP API.Net
JDBC
ODBC
WebSocket
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGoClojure
Java
Java
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsuser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoBy using transaction functionsyesyes, 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 peersMulti-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 methodsnonoyes infoHadoop integrationno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnonoAccess 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
BoltDBDatomicEXASOLVertica 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
BoltDBDatomicEXASOLVertica infoOpenText™ Vertica™
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