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DBMS > Amazon Aurora vs. Apache Impala vs. Drizzle vs. Google Cloud Datastore vs. IBM Cloudant

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Drizzle vs. Google Cloud Datastore vs. IBM Cloudant

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Cloudant  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering based on Apache CouchDB
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeDocument store
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.50
Rank#49  Overall
#31  Relational DBMS
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score2.73
Rank#108  Overall
#20  Document stores
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­cloudant
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docscloud.ibm.com/­docs/­Cloudant
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerGoogleIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release20152013200820082010
Current release4.1.0, June 20227.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Erlang
Server operating systemshostedLinuxFreeBSD
Linux
OS X
hostedhosted
Data schemeyesyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details hereno
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.yesnonono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenousing Google App EngineView functions (Map-Reduce) in JavaScript
Triggersyesnono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowyes
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.Eventual Consistency
Foreign keys infoReferential integrityyesnoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a document possible
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoOptimistic locking
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.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per database

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More resources
Amazon AuroraApache ImpalaDrizzleGoogle Cloud DatastoreIBM Cloudant
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