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DBMS > Bangdb vs. HEAVY.AI vs. Ingres vs. InterSystems IRIS vs. Vertica

System Properties Comparison Bangdb vs. HEAVY.AI vs. Ingres vs. InterSystems IRIS vs. Vertica

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIngres  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareWell established RDBMSA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityCloud 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
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.15
Rank#334  Overall
#45  Document stores
#31  Graph DBMS
#31  Time Series DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score4.67
Rank#77  Overall
#42  Relational DBMS
Score4.39
Rank#81  Overall
#13  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#44  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitebangdb.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.actian.com/­databases/­ingreswww.intersystems.com/­products/­intersystems-iriswww.vertica.com
Technical documentationdocs.bangdb.comdocs.heavy.aidocs.actian.com/­ingresdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsvertica.com/­documentation
DeveloperSachin Sinha, BangDBHEAVY.AI, Inc.Actian CorporationInterSystemsOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220161974 infooriginally developed at University Berkely in early 1970s20182005
Current releaseBangDB 2.0, October 20215.10, January 202211.2, May 20222023.3, June 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2; enterprise edition availablecommercialcommercialcommercial 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, C++C++ and CUDACC++
Server operating systemsLinuxLinuxAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
AIX
Linux
macOS
Ubuntu
Windows
Linux
Data schemeschema-freeyesyesdepending on used data modelYes, 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 dateyes: string, long, double, int, geospatial, stream, eventsyesyesyesyes
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 infobut tools for importing/exporting data from/to XML-files availableyesno
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL like support with command line toolyesyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Java
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C++
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes, Notifications (with Streaming only)noyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infoRound robinhorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replicationIngres ReplicatorSource-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 systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes infoMVCCyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesnoyesno
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BangdbHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IngresInterSystems IRISVertica infoOpenText™ Vertica™
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more
Deploy-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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
BangdbHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IngresInterSystems IRISVertica infoOpenText™ Vertica™
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