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DBMS > Amazon DocumentDB vs. Faircom DB vs. Google Cloud Datastore vs. TerarkDB

System Properties Comparison Amazon DocumentDB vs. Faircom DB vs. Google Cloud Datastore vs. TerarkDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeKey-value store
Relational DBMS
Document storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.04
Rank#377  Overall
#58  Key-value stores
Websiteaws.amazon.com/­documentdbwww.faircom.com/­products/­faircom-dbcloud.google.com/­datastoregithub.com/­bytedance/­terarkdb
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­datastore/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperFairCom CorporationGoogleByteDance, originally Terark
Initial release2019197920082016
Current releaseV12, November 2020
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C++
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hosted
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes, details hereno
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsSQL-like query language (GQL)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Java API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++using Google App Engineno
TriggersnoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, 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 using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate 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 integrityno infotypically not used, however similar functionality with DBRef possibleyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationstunable from ACID to Eventually ConsistentACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon DocumentDBFaircom DB infoformerly c-treeACEGoogle Cloud DatastoreTerarkDB
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