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DBMS > Databricks vs. HEAVY.AI vs. Vertica

System Properties Comparison Databricks vs. HEAVY.AI vs. Vertica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareCloud 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
Relational DBMS
Relational 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
Score83.29
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.52
Rank#147  Overall
#67  Relational DBMS
Score9.96
Rank#42  Overall
#26  Relational DBMS
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.vertica.com
Technical documentationdocs.databricks.comdocs.heavy.aivertica.com/­documentation
DeveloperDatabricksHEAVY.AI, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320162005
Current release5.10, January 202212.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono 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 languageC++ and CUDAC++
Server operating systemshostedLinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesYes, 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 dateyesyes
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.yesnono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLwith Databricks SQLyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source 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 methodsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Vertica infoOpenText™ Vertica™
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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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,...
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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
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Vertica infoOpenText™ Vertica™
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