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DBMS > Amazon Neptune vs. EventStoreDB vs. Google BigQuery

System Properties Comparison Amazon Neptune vs. EventStoreDB vs. Google BigQuery

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEventStoreDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudIndustrial-strength, open-source database solution built from the ground up for event sourcing.Large scale data warehouse service with append-only tables
Primary database modelGraph DBMS
RDF store
Event StoreRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.82
Rank#109  Overall
#9  Graph DBMS
#5  RDF stores
Score1.29
Rank#174  Overall
#1  Event Stores
Score62.67
Rank#19  Overall
#13  Relational DBMS
Websiteaws.amazon.com/­neptunewww.eventstore.comcloud.google.com/­bigquery
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdevelopers.eventstore.comcloud.google.com/­bigquery/­docs
DeveloperAmazonEvent Store LimitedGoogle
Initial release201720122010
Current release21.2, February 2021
License infoCommercial or Open SourcecommercialOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Server operating systemshostedLinux
Windows
hosted
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesnono
SQL infoSupport of SQLnoyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScript
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnonenone
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying data
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)

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More resources
Amazon NeptuneEventStoreDBGoogle BigQuery
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