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DBMS > Datomic vs. Hypertable vs. Tarantool vs. Vertica

System Properties Comparison Datomic vs. Hypertable vs. Tarantool vs. Vertica

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHypertable  Xexclude from comparisonTarantool  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn open source BigTable implementation based on distributed file systems such as HadoopIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsCloud or on-premises 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 DBMSWide column storeKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Relational DBMS
Spatial DBMS infowith Tarantool/GIS extension
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#133  Overall
#66  Relational DBMS
Score1.77
Rank#143  Overall
#27  Key-value stores
Score19.85
Rank#38  Overall
#23  Relational DBMS
Websitewww.datomic.comwww.tarantool.iowww.vertica.com
Technical documentationdocs.datomic.comwww.tarantool.io/­en/­docvertica.com/­documentation
DeveloperCognitectHypertable Inc.VKMicro Focus infoprior to that Hewlett Packard
Initial release2012200920082005
Current release1.0.6362, January 20220.9.8.11, March 20162.10.0, May 202211.1, February 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU version 3. Commercial license availableOpen Source infoBSDcommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageJava, ClojureC++C and C++C++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
BSD
Linux
macOS
Linux
Data schemeyesschema-freeschema-free, schema definition possibleyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesnostring, double, decimal, uuid, integer, blob, booleanyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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.nonono
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesNo Indexes Required
SQL infoSupport of SQLnonoFull-featured ANSI SQL supportFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIC++ API
Thrift
Open binary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoLua, C and SQL stored proceduresyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingHash sharding based on virtual bucketshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factor on file system levelMulti-source replication
Source-replica replication
Multi-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 methodsnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes, with SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes, regular snapshots on disk, write ahead loggingyes
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 developmentyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlnonoAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicHypertableTarantoolVertica infoVertica Analytics Platform
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantagesFast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
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...
» more

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More resources
DatomicHypertableTarantoolVertica infoVertica Analytics Platform
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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