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DBMS > Amazon DocumentDB vs. FeatureBase vs. Google Cloud Datastore vs. GridGain vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. FeatureBase vs. Google Cloud Datastore vs. GridGain vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMSDocument storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.featurebase.comcloud.google.com/­datastorewww.gridgain.comyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.featurebase.comcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.html
DeveloperMolecula and Pilosa Open Source ContributorsGoogleGridGain Systems, Inc.Q2WEB GmbH
Initial release20192017200820072009
Current release2022, May 2022GridGain 8.5.1
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, C++, .Net
Server operating systemshostedLinux
macOS
hostedLinux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.nononoyesno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLnoSQL queriesSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC
JDBC
Kafka Connector
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)
TriggersnonoCallbacks using the Google Apps Engineyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replication using Paxosyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBFeatureBaseGoogle Cloud DatastoreGridGainYaacomo
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