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DBMS > Apache Druid vs. Prometheus vs. RisingWave vs. Spark SQL

System Properties Comparison Apache Druid vs. Prometheus vs. RisingWave vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonPrometheus  Xexclude from comparisonRisingWave  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataOpen-source Time Series DBMS and monitoring systemA distributed RDBMS for stream processing, wire-compatible with PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.58
Rank#242  Overall
#111  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgprometheus.iowww.risingwave.com/­databasespark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designprometheus.io/­docsdocs.risingwave.com/­docs/­current/­introspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsRisingWave LabsApache Software Foundation
Initial release2012201520222014
Current release29.0.1, April 20241.2, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoRustScala
Server operating systemsLinux
OS X
Unix
Linux
Windows
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyStandard SQL-types and JSONyes
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.nono infoImport of XML data possiblenono
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL for queryingnoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoUDFs in Python or Javano
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoUsers and Rolesno

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More resources
Apache DruidPrometheusRisingWaveSpark SQL
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