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DBMS > CrateDB vs. HEAVY.AI vs. STSdb vs. UniData,UniVerse vs. Vertica

System Properties Comparison CrateDB vs. HEAVY.AI vs. STSdb vs. UniData,UniVerse vs. Vertica

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSTSdb  Xexclude from comparisonUniData,UniVerse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionDistributed Database based on LuceneA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodMultiValue database and application server with SQL mapping layer and meta database capabilitiesCloud 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 modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSKey-value storeMultivalue DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitecratedb.comgithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­STSSoft/­STSdb4www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidatawww.vertica.com
Technical documentationcratedb.com/­docsdocs.heavy.aidocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidatavertica.com/­documentation
DeveloperCrateHEAVY.AI, Inc.STS Soft SCRocket SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132016201119852005
Current release5.10, January 20224.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGPLv2, commercial license availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono 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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++ and CUDAC#CC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxWindowsAIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-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 dateyesyesyes infoprimitive types and user defined types (classes)optionalyes
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 indexesyesnonoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
.NET Client APIJava API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
All languages supporting JDBC/ODBC/Thrift
Python
C#
Java
.Net
Basic infoU2 Basic
C
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions (Javascript)nonoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes infoU2 Basicyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinnonenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replicationnoneSource-replica replicationMulti-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 methodsnonononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynonoACID infoconfigurableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardnoAccess rights according to SQL-standard and operating system basedfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CrateDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022STSdbUniData,UniVerseVertica infoOpenText™ Vertica™
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
CrateDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022STSdbUniData,UniVerseVertica infoOpenText™ Vertica™
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