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DBMS > Amazon Neptune vs. Google Cloud Datastore vs. Sphinx vs. YDB

System Properties Comparison Amazon Neptune vs. Google Cloud Datastore vs. Sphinx vs. YDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSphinx  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen source search engine for searching in data from different sources, e.g. relational databasesA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelGraph DBMS
RDF store
Document storeSearch engineDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score4.47
Rank#76  Overall
#12  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­datastoresphinxsearch.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­datastore/­docssphinxsearch.com/­docsydb.tech/­en/­docs
DeveloperAmazonGoogleSphinx Technologies Inc.Yandex
Initial release2017200820012019
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes, details herenoyes
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.nonono
Secondary indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (SphinxQL)SQL-like query language (YQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocolRESTful HTTP API (DynamoDB compatible)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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 PaxosnoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes 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 Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess 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)noAccess rights defined for Yandex Cloud users

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More resources
Amazon NeptuneGoogle Cloud DatastoreSphinxYDB
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