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DBMS > Amazon Neptune vs. EsgynDB vs. Google Cloud Datastore vs. HEAVY.AI vs. OrigoDB

System Properties Comparison Amazon Neptune vs. EsgynDB vs. Google Cloud Datastore vs. HEAVY.AI vs. OrigoDB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA fully ACID in-memory object graph database
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeRelational DBMSDocument store
Object oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Websiteaws.amazon.com/­neptunewww.esgyn.cncloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
origodb.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­datastore/­docsdocs.heavy.aiorigodb.com/­docs
DeveloperAmazonEsgynGoogleHEAVY.AI, Inc.Robert Friberg et al
Initial release20172015200820162009 infounder the name LiveDB
Current release5.10, January 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++ and CUDAC#
Server operating systemshostedLinuxhostedLinuxLinux
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesUser defined using .NET types and collections
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.nonononono infocan be achieved using .NET
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yesno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
.NET Client API
HTTP API
LINQ
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App Enginenoyes
TriggersnonoCallbacks using the Google Apps Enginenoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoRound robinhorizontal partitioning infoclient side managed; servers are not synchronized
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 between multi datacentersMulti-source replication using PaxosMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownono
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.Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes infovia ReferenceProperties or Ancestor pathsnodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole based authorization

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More resources
Amazon NeptuneEsgynDBGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022OrigoDB
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