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DBMS > Databricks vs. TypeDB vs. Vertica

System Properties Comparison Databricks vs. TypeDB vs. Vertica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonTypeDB infoformerly named Grakn  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.TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.Cloud 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
Graph DBMS infoThe type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS infoThe data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS infoThe type-theoretic data model of TypeDB subsumes the relational database model.
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score0.59
Rank#233  Overall
#20  Graph DBMS
#10  Object oriented DBMS
#107  Relational DBMS
Score9.78
Rank#42  Overall
#26  Relational DBMS
Websitewww.databricks.comtypedb.comwww.vertica.com
Technical documentationdocs.databricks.comtypedb.com/­docsvertica.com/­documentation
DeveloperDatabricksVaticleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320162005
Current release2.28.3, June 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL Version 3, commercial licenses 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 languageJavaC++
Server operating systemshostedLinux
OS X
Windows
Linux
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 indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLwith Databricks SQLnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPython
R
Scala
All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust
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 nodesnohorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSynchronous replication via raftMulti-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 integrityno infosubstituted by the relationship featureyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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.nonono
User concepts infoAccess controlyes infoat REST API level; other APIs in progressfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
DatabricksTypeDB infoformerly named GraknVertica infoOpenText™ Vertica™
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