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DBMS > Apache Hive vs. Couchbase vs. Databricks

System Properties Comparison Apache Hive vs. Couchbase vs. Databricks

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonCouchbase infoOriginally called Membase  Xexclude from comparisonDatabricks  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile databaseThe 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.
Primary database modelRelational DBMSDocument store
Vector DBMS
Document store
Relational DBMS
Secondary database modelsKey-value store infooriginating from the former Membase product and supporting the Memcached protocol
Spatial DBMS infousing the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.49
Rank#18  Overall
#12  Relational DBMS
Score15.63
Rank#35  Overall
#5  Document stores
#2  Vector DBMS
Score90.03
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Websitehive.apache.orgwww.couchbase.comwww.databricks.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.couchbase.comdocs.databricks.com
DeveloperApache Software Foundation infoinitially developed by FacebookCouchbase, Inc.Databricks
Initial release201220112013
Current release3.1.3, April 2022Server: 7.6, March 2024; Mobile: 3.3, August 2024; Couchbase Capella (DBaaS), September 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBusiness Source License (BSL 1.1); Commercial licenses also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, Go and Erlang
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
hosted
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes
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.yes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use caseswith Databricks SQL
APIs and other access methodsJDBC
ODBC
Thrift
CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
PHP
Python
.Net
C
Go
Java
JavaScript infoNode.js
Kotlin
PHP
Python
Ruby
Scala
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceFunctions and timers in JavaScript and UDFs in Java, Python, SQL++user defined functions and aggregates
Triggersnoyes infovia the TAP protocol
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infoincluding cross data center replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency infoselectable on a per-operation basis
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.yes infoEphemeral bucketsno
User concepts infoAccess controlAccess rights for users, groups and rolesUser and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.
More information provided by the system vendor
Apache HiveCouchbase infoOriginally called MembaseDatabricks
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache HiveCouchbase infoOriginally called MembaseDatabricks
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