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DBMS > Google Cloud Datastore vs. Kinetica vs. Neo4j

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Neo4j

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelDocument storeRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score44.47
Rank#23  Overall
#1  Graph DBMS
Websitecloud.google.com/­datastorewww.kinetica.comneo4j.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comneo4j.com/­docs
DeveloperGoogleKineticaNeo4j, Inc.
Initial release200820122007
Current release7.1, August 20215.19, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version3, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageC, C++Java, Scala
Server operating systemshostedLinuxLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeschema-freeyesschema-free and schema-optional
Typing infopredefined data types such as float or dateyes, details hereyesyes
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 indexesyesyesyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyes infoUser defined Procedures and Functions
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual Consistency depending on configurationCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Google Cloud DatastoreKineticaNeo4j
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
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