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

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonFast, reliable graph database built for the cloudHigh-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 grid
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMSDocument storeKey-value 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
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
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
Websiteaws.amazon.com/­rds/­auroraaws.amazon.com/­neptunewww.exasol.comcloud.google.com/­datastorehazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlaws.amazon.com/­neptune/­developer-resourceswww.exasol.com/­resourcescloud.google.com/­datastore/­docshazelcast.org/­imdg/­docs
DeveloperAmazonAmazonExasolGoogleHazelcast
Initial release20152017200020082008
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache Version 2; commercial licenses available
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 systemshostedhostedhostedAll OS with a Java VM
Data schemeyesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, 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.yesnononoyes infothe object must implement a serialization strategy
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesnoyesSQL-like query language (GQL)SQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP 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
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesnouser defined functionsusing Google App Engineyes infoEvent Listeners, Executor Services
TriggersyesnoyesCallbacks using the Google Apps Engineyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source replication using Paxosyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 Algorithm
Foreign keys infoReferential integrityyesyes infoRelationships in graphsyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access 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 control

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More resources
Amazon AuroraAmazon NeptuneEXASOLGoogle Cloud DatastoreHazelcast
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