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DBMS > AgensGraph vs. Google Cloud Datastore vs. HEAVY.AI vs. Lovefield vs. VelocityDB

System Properties Comparison AgensGraph vs. Google Cloud Datastore vs. HEAVY.AI vs. Lovefield vs. VelocityDB

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAutomatically 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 hardwareEmbeddable relational database for web apps written in pure JavaScriptA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelGraph DBMS
Relational DBMS
Document storeRelational DBMSRelational DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#320  Overall
#29  Graph DBMS
#143  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score0.00
Rank#385  Overall
#40  Graph DBMS
#21  Object oriented DBMS
Websitebitnine.net/­agensgraphcloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldvelocitydb.com
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docsdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdvelocitydb.com/­UserGuide
DeveloperBitnine Global Inc.GoogleHEAVY.AI, Inc.GoogleVelocityDB Inc
Initial release20162008201620142011
Current release2.1, December 20185.10, January 20222.1.12, February 20177.x
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++ and CUDAJavaScriptC#
Server operating systemsLinux
OS X
Windows
hostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAny that supports .NET
Data schemedepending on used data modelschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yesSQL-like query language infovia JavaScript builder patternno
APIs and other access methodsCypher Query Language
JDBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
.Net
Supported programming languagesC
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
JavaScript.Net
Server-side scripts infoStored proceduresyesusing Google App Enginenonono
TriggersnoCallbacks using the Google Apps EnginenoUsing read-only observersCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding infoRound robinnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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 integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infousing MemoryDByes
User concepts infoAccess controlfine 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-standardnoBased on Windows Authentication

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More resources
AgensGraphGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldVelocityDB
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