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DBMS > Databend vs. Hive vs. IBM Db2 Event Store vs. Prometheus vs. Quasardb

System Properties Comparison Databend vs. Hive vs. IBM Db2 Event Store vs. Prometheus vs. Quasardb

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonHive  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPrometheus  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexitydata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed Event Store optimized for Internet of Things use casesOpen-source Time Series DBMS and monitoring systemDistributed, high-performance timeseries database
Primary database modelRelational DBMSRelational DBMSEvent Store
Time Series DBMS
Time Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
hive.apache.orgwww.ibm.com/­products/­db2-event-storeprometheus.ioquasar.ai
Technical documentationdocs.databend.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-storeprometheus.io/­docsdoc.quasar.ai/­master
DeveloperDatabend LabsApache Software Foundation infoinitially developed by FacebookIBMquasardb
Initial release20212012201720152009
Current release1.0.59, April 20233.1.3, April 20222.03.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial infofree developer edition availableOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaC and C++GoC++
Server operating systemshosted
Linux
macOS
All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
Windows
BSD
Linux
OS X
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesNumeric data onlyyes infointeger and binary
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.nonono infoImport of XML data possibleno
Secondary indexesnoyesnonoyes infowith tags
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimenoSQL-like query language
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIHTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesnono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorActive-active shard replicationyes infoby FederationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and rolesfine grained access rights according to SQL-standardnoCryptographically strong user authentication and audit trail

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