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DBMS > Databricks vs. Ignite vs. Linter vs. Vertica

System Properties Comparison Databricks vs. Ignite vs. Linter vs. Vertica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIgnite  Xexclude from comparisonLinter  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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.RDBMS for high security requirementsCloud 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
Key-value 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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.databricks.comignite.apache.orglinter.ruwww.vertica.com
Technical documentationdocs.databricks.comapacheignite.readme.io/­docsvertica.com/­documentation
DeveloperDatabricksApache Software Foundationrelex.ruOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201519902005
Current releaseApache Ignite 2.612.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono 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++, Java, .NetC and C++C++
Server operating systemshostedLinux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesYes, 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
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.yesyesnono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yes infoproprietary syntax with the possibility to convert from PL/SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes (cache interceptors and events)yesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)Source-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 methodsyes (compute grid and hadoop accelerator)nono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsfine 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
DatabricksIgniteLinterVertica 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
DatabricksIgniteLinterVertica infoOpenText™ Vertica™
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