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DBMS > Amazon CloudSearch vs. Amazon Neptune vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. OpenEdge

System Properties Comparison Amazon CloudSearch vs. Amazon Neptune vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. OpenEdge

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudFast, reliable graph database built for the cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management system
Primary database modelSearch engineGraph DBMS
RDF store
Document storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score4.47
Rank#76  Overall
#12  Document stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Websiteaws.amazon.com/­cloudsearchaws.amazon.com/­neptunecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedge
Technical documentationdocs.aws.amazon.com/­cloudsearchaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­datastore/­docsdocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperAmazonAmazonGoogleMicrosoftProgress Software Corporation
Initial release20122017200820121984
Current releaseOpenEdge 12.2, March 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhostedhostedhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.nononoyes
Secondary indexesyes infoall search fields are automatically indexednoyesnoyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)noyes infoclose to SQL 92
APIs and other access methodsHTTP APIOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)
Server-side scripts infoStored proceduresnonousing Google App Enginenoyes
TriggersnonoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requirednoneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSMulti-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 infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID
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.nonono
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesUsers and groups

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More resources
Amazon CloudSearchAmazon NeptuneGoogle Cloud DatastoreMicrosoft Azure Table StorageOpenEdge
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