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DBMS > Amazon Aurora vs. EXASOL vs. Google Cloud Datastore vs. Hazelcast vs. PouchDB

System Properties Comparison Amazon Aurora vs. EXASOL vs. Google Cloud Datastore vs. Hazelcast vs. PouchDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value storeDocument store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score2.28
Rank#115  Overall
#21  Document stores
Websiteaws.amazon.com/­rds/­aurorawww.exasol.comcloud.google.com/­datastorehazelcast.compouchdb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­resourcescloud.google.com/­datastore/­docshazelcast.org/­imdg/­docspouchdb.com/­guides
DeveloperAmazonExasolGoogleHazelcastApache Software Foundation
Initial release20152000200820082012
Current release5.3.6, November 20237.1.1, June 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source
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 languageJavaJavaScript
Server operating systemshostedhostedAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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.yesnonoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyesyes infovia views
SQL infoSupport of SQLyesyesSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript 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
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
JavaScript
Server-side scripts infoStored proceduresyesuser defined functionsusing Google App Engineyes infoEvent Listeners, Executor ServicesView functions in JavaScript
TriggersyesyesCallbacks using the Google Apps Engineyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosyes infoReplicated MapMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflowyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 AlgorithmEventual Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlno

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More resources
Amazon AuroraEXASOLGoogle Cloud DatastoreHazelcastPouchDB
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