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DBMS > Amazon DocumentDB vs. Databricks vs. Faircom DB vs. PouchDB

System Properties Comparison Amazon DocumentDB vs. Databricks vs. Faircom DB vs. PouchDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceThe 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.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.JavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument storeDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websiteaws.amazon.com/­documentdbwww.databricks.comwww.faircom.com/­products/­faircom-dbpouchdb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlpouchdb.com/­guides
DeveloperDatabricksFairCom CorporationApache Software Foundation
Initial release2019201319792012
Current releaseV12, November 20207.1.1, June 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial infoRestricted, free version availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaScript
Server operating systemshostedhostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresno
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.noyesnono
Secondary indexesyesyesyesyes infovia views
SQL infoSupport of SQLnowith Databricks SQLyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Python
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
JavaScript
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes info.Net, JavaScript, C/C++View functions in JavaScript
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDtunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users and rolesFine grained access rights according to SQL-standard with additional protections for filesno
More information provided by the system vendor
Amazon DocumentDBDatabricksFaircom DB infoformerly c-treeACEPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DocumentDBDatabricksFaircom DB infoformerly c-treeACEPouchDB
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