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DBMS > 4D vs. Databricks vs. LeanXcale vs. VictoriaMetrics

System Properties Comparison 4D vs. Databricks vs. LeanXcale vs. VictoriaMetrics

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonDatabricks  Xexclude from comparisonLeanXcale  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemThe 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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitewww.4d.comwww.databricks.comwww.leanxcale.comvictoriametrics.com
Technical documentationdeveloper.4d.comdocs.databricks.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
Developer4D, IncDatabricksLeanXcaleVictoriaMetrics
Initial release1984201320152018
Current releasev20, April 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGo
Server operating systemsOS X
Windows
hostedFreeBSD
Linux
macOS
OpenBSD
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyes
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.yesyesno
Secondary indexesyesyes
SQL infoSupport of SQLyes infoclose to SQL 92with Databricks SQLyes infothrough Apache Derbyno
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages4D proprietary IDE
PHP
Python
R
Scala
C
Java
Scala
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.nonoyesno
User concepts infoAccess controlUsers and groups
More information provided by the system vendor
4D infoformer name: 4th DimensionDatabricksLeanXcaleVictoriaMetrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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4D infoformer name: 4th DimensionDatabricksLeanXcaleVictoriaMetrics
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