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DBMS > Databricks vs. PostGIS vs. StarRocks vs. Vertica

System Properties Comparison Databricks vs. PostGIS vs. StarRocks vs. Vertica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPostGIS  Xexclude from comparisonStarRocks  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.Spatial extension of PostgreSQLAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache DorisCloud 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
Spatial DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score1.04
Rank#189  Overall
#88  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.databricks.compostgis.netwww.starrocks.iowww.vertica.com
Technical documentationdocs.databricks.compostgis.net/­documentationdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_introvertica.com/­documentation
DeveloperDatabricksThe Linux Foundation infosince Feb 2023OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013200520202005
Current release3.4.2, February 20242.5.3, March 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoApache Version 2.0commercial 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 languageCC++, JavaC++
Server operating systemshostedLinuxLinux
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 SQLyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
MySQL protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPython
R
Scala
JavaC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsuser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes infobased on PostgreSQLhorizontal partitioning (by range and hash)horizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infobased on PostgreSQLMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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.nononono
User concepts infoAccess controlyes infobased on PostgreSQLRole based access control and fine grained access rightsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatabricksPostGISStarRocksVertica 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
DatabricksPostGISStarRocksVertica infoOpenText™ Vertica™
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