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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. Hazelcast vs. TDSQL for MySQL vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. Hazelcast vs. TDSQL for MySQL vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonTDSQL for MySQL  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 serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeDocument storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastorehazelcast.comwww.tencentcloud.com/­products/­dcdbyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docshazelcast.org/­imdg/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleHazelcastTencentQ2WEB GmbH
Initial release20192008200820132009
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedAll OS with a Java VMhostedAndroid
Linux
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nonoyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageyesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyes infoEvent Listeners, Executor Servicesyes
TriggersnoCallbacks using the Google Apps Engineyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingAutomatic shardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication using Paxosyes infoReplicated MapMulti-source replication
Source-replica replication
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 Dataflowyesnono
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 Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBGoogle Cloud DatastoreHazelcastTDSQL for MySQLYaacomo
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