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DBMS > FoundationDB vs. HBase vs. HEAVY.AI vs. UniData,UniVerse vs. Vertica

System Properties Comparison FoundationDB vs. HBase vs. HEAVY.AI vs. UniData,UniVerse vs. Vertica

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonHBase  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonUniData,UniVerse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.Wide-column store based on Apache Hadoop and on concepts of BigTableA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareMultiValue 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 infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Wide column storeRelational DBMSMultivalue DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­apple/­foundationdbhbase.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidatawww.vertica.com
Technical documentationapple.github.io/­foundationdbhbase.apache.org/­book.htmldocs.heavy.aidocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidatavertica.com/­documentation
DeveloperFoundationDBApache Software Foundation infoApache top-level project, originally developed by PowersetHEAVY.AI, Inc.Rocket SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132008201619852005
Current release6.2.28, November 20202.3.4, January 20215.10, January 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache Version 2; enterprise edition 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.
Implementation languageC++JavaC++ and CUDACC++
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
LinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemeschema-free infosome layers support schemasschema-free, schema definition possibleyesschema-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 dateno infosome layers support typingoptions to bring your own types, AVROyesoptionalyes
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 indexesnononoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLsupported in specific SQL layer onlynoyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Vega
Java 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
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C
C#
C++
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Basic infoU2 Basic
C
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresin SQL-layer onlyyes infoCoprocessors in Javanoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnoyes infoU2 Basicyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoRound robinnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replicationSource-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 methodsnoyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)noACID 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.yesyesno
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardAccess 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
FoundationDBHBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022UniData,UniVerseVertica 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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More resources
FoundationDBHBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022UniData,UniVerseVertica infoOpenText™ Vertica™
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