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DBMS > Amazon DocumentDB vs. Apache Impala vs. Google Cloud Datastore vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. Google Cloud Datastore vs. Yaacomo

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Datastore  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 serviceAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Websiteaws.amazon.com/­documentdbimpala.apache.orgcloud.google.com/­datastoreyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleQ2WEB GmbH
Initial release2019201320082009
Current release4.1.0, June 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedLinuxhostedAndroid
Linux
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (GQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceusing Google App Engine
TriggersnonoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBApache ImpalaGoogle Cloud DatastoreYaacomo
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