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DBMS > CouchDB vs. Databricks vs. Google Cloud Datastore vs. Manticore Search

System Properties Comparison CouchDB vs. Databricks vs. Google Cloud Datastore vs. Manticore Search

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.
Primary database modelDocument storeDocument store
Relational DBMS
Document storeSearch engine
Secondary database modelsSpatial DBMS infousing the Geocouch extensionTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.30
Rank#45  Overall
#7  Document stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.22
Rank#312  Overall
#21  Search engines
Websitecouchdb.apache.orgwww.databricks.comcloud.google.com/­datastoremanticoresearch.com
Technical documentationdocs.couchdb.org/­en/­stabledocs.databricks.comcloud.google.com/­datastore/­docsmanual.manticoresearch.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerDatabricksGoogleManticore Software
Initial release2005201320082017
Current release3.3.3, December 20236.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedhostedFreeBSD
Linux
macOS
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema
Typing infopredefined data types such as float or datenoyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.noyesnoCan index from XML
Secondary indexesyes infovia viewsyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnowith Databricks SQLSQL-like query language (GQL)SQL-like query language
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresView functions in JavaScriptuser defined functions and aggregatesusing Google App Engineuser defined functions
TriggersyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-source replication using PaxosSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
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 can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatabricksGoogle Cloud DatastoreManticore Search
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"DatabricksGoogle Cloud DatastoreManticore Search
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