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DBMS > Apache Impala vs. Databricks vs. VictoriaMetrics

System Properties Comparison Apache Impala vs. Databricks vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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 fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSDocument store
Relational DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websiteimpala.apache.orgwww.databricks.comvictoriametrics.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksVictoriaMetrics
Initial release201320132018
Current release4.1.0, June 2022v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Go
Server operating systemsLinuxhostedFreeBSD
Linux
macOS
OpenBSD
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)
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.noyesno
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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 controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos
More information provided by the system vendor
Apache ImpalaDatabricksVictoriaMetrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksVictoriaMetrics
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