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DBMS > Amazon Neptune vs. GeoSpock vs. Google Cloud Datastore vs. Oracle Berkeley DB

System Properties Comparison Amazon Neptune vs. GeoSpock vs. Google Cloud Datastore vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudSpatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value store
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score4.13
Rank#71  Overall
#12  Document stores
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­neptunegeospock.comcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonGeoSpockGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release201720081994
Current release2.0, September 201918.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, 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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesnotemporal, categoricalyesyes
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)SQL-like query language (GQL)yes infoSQL interfaced based on SQLite is available
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresnonousing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingnone
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 PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
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.
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon NeptuneGeoSpockGoogle Cloud DatastoreOracle Berkeley DB
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