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DBMS > Amazon DocumentDB vs. BigObject vs. Faircom EDGE vs. Google Cloud Datastore

System Properties Comparison Amazon DocumentDB vs. BigObject vs. Faircom EDGE vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBigObject  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for real-time computations and queriesFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument storeRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteaws.amazon.com/­documentdbbigobject.iowww.faircom.com/­products/­faircom-edgecloud.google.com/­datastore
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.bigobject.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­datastore/­docs
DeveloperBigObject, Inc.FairCom CorporationGoogle
Initial release2019201519792008
Current releaseV3, October 2020
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Android
Linux infoARM, x86
Raspbian
Windows
hosted
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes, details here
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.nonoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoANSI SQL queriesSQL-like query language (GQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)fluentd
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoLuayes info.Net, JavaScript, C/C++using Google App Engine
TriggersnonoyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnonenoneFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Tunable Consistency
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 possibleyes infoautomatically between fact table and dimension tablesyes infowhen using SQLyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users and rolesnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon DocumentDBBigObjectFaircom EDGE infoformerly c-treeEDGEGoogle Cloud Datastore
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