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DBMS > Databricks vs. NSDb vs. TimesTen vs. Vertica

System Properties Comparison Databricks vs. NSDb vs. TimesTen vs. Vertica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  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.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.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
Time Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitewww.databricks.comnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.htmlwww.vertica.com
Technical documentationdocs.databricks.comnsdb.io/­Architecturedocs.oracle.com/­en/­database/­other-databases/­timesten/­index.htmlvertica.com/­documentation
DeveloperDatabricksOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201719982005
Current releaseRelease 22.112.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 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 languageJava, ScalaC++
Server operating systemshostedLinux
macOS
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
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 dateyes: int, bigint, decimal, stringyesyes
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.yesnonono
Secondary indexesyesall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPython
R
Scala
Java
Scala
C
C++
Java
Node.js
PL/SQL
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoPL/SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, 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 nodesyesMulti-source replication
Source-replica replication
Multi-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 ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes infoby means of logfiles and checkpointsyes
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
DatabricksNSDbTimesTenVertica infoOpenText™ Vertica™
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksNSDbTimesTenVertica infoOpenText™ Vertica™
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