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DBMS > AnzoGraph DB vs. Google Cloud Datastore vs. Google Cloud Firestore vs. Kinetica

System Properties Comparison AnzoGraph DB vs. Google Cloud Datastore vs. Google Cloud Firestore vs. Kinetica

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Fully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
RDF store
Document storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score4.13
Rank#71  Overall
#12  Document stores
Score6.63
Rank#54  Overall
#9  Document stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Websitecambridgesemantics.com/­anzographcloud.google.com/­datastorefirebase.google.com/­products/­firestorewww.kinetica.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­datastore/­docsfirebase.google.com/­docs/­firestoredocs.kinetica.com
DeveloperCambridge SemanticsGoogleGoogleKinetica
Initial release2018200820172012
Current release2.3, January 20217.1, August 2021
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinuxhostedhostedLinux
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyes
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.nononono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineyes, Firebase Rules & Cloud Functionsuser defined functions
TriggersnoCallbacks using the Google Apps Engineyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication using PaxosMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infousing Google Cloud DataflowUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate 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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infonot needed in graphsyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and roles on table level

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More resources
AnzoGraph DBGoogle Cloud DatastoreGoogle Cloud FirestoreKinetica
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