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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. Google Cloud Spanner vs. GridGain vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. Google Cloud Spanner vs. GridGain vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Spanner  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 serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.GridGain 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 DBMSRelational DBMSKey-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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgcloud.google.com/­spannerwww.gridgain.comyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgcloud.google.com/­spanner/­docswww.gridgain.com/­docs/­index.html
DeveloperApache Software FoundationGoogleGridGain Systems, Inc.Q2WEB GmbH
Initial release20192014201720072009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019GridGain 8.5.1
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialcommercial
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 languageJavaJava, C++, .Net
Server operating systemshostedLinux
Unix
Windows
hostedLinux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLnoyesyes infoQuery statements complying to ANSI 2011ANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP 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
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes (compute grid and cache interceptors can be used instead)
Triggersnononoyes (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 replicasMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.yes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infoStrict serializable isolationACIDACID
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.yesnoyesyes
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess 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 DocumentDBApache PhoenixGoogle Cloud SpannerGridGainYaacomo
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