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DBMS > Databricks vs. LevelDB vs. VictoriaMetrics

System Properties Comparison Databricks vs. LevelDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLevelDB  Xexclude from comparisonVictoriaMetrics  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument store
Relational DBMS
Key-value storeTime 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
Score2.25
Rank#115  Overall
#19  Key-value stores
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitewww.databricks.comgithub.com/­google/­leveldbvictoriametrics.com
Technical documentationdocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperDatabricksGoogleVictoriaMetrics
Initial release201320112018
Current release1.23, February 2021v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Go
Server operating systemshostedIllumos
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateno
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 indexesyesno
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlno
More information provided by the system vendor
DatabricksLevelDBVictoriaMetrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLevelDBVictoriaMetrics
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