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DBMS > CouchDB vs. Databricks vs. H2 vs. Hazelcast vs. Prometheus

System Properties Comparison CouchDB vs. Databricks vs. H2 vs. Hazelcast vs. Prometheus

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatabricks  Xexclude from comparisonH2  Xexclude from comparisonHazelcast  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.The 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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A widely adopted in-memory data gridOpen-source Time Series DBMS and monitoring system
Primary database modelDocument storeDocument store
Relational DBMS
Relational DBMSKey-value storeTime Series DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionSpatial DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score8.33
Rank#46  Overall
#30  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitecouchdb.apache.orgwww.databricks.comwww.h2database.comhazelcast.comprometheus.io
Technical documentationdocs.couchdb.org/­en/­stabledocs.databricks.comwww.h2database.com/­html/­main.htmlhazelcast.org/­imdg/­docsprometheus.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerDatabricksThomas MuellerHazelcast
Initial release20052013200520082015
Current release3.3.3, December 20232.2.220, July 20235.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJavaJavaGo
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VMAll OS with a Java VMLinux
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesNumeric data only
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.noyesnoyes infothe object must implement a serialization strategyno infoImport of XML data possible
Secondary indexesyes infovia viewsyesyesyesno
SQL infoSupport of SQLnowith Databricks SQLyesSQL-like query languageno
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Python
R
Scala
Java.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functions and aggregatesJava Stored Procedures and User-Defined Functionsyes infoEvent Listeners, Executor Servicesno
Triggersyesyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0noneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes infoReplicated Mapyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithmnone
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACIDACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesno
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardRole-based access controlno
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksH2HazelcastPrometheus
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksH2HazelcastPrometheus
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