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DBMS > AnzoGraph DB vs. Cloudflare Workers KV vs. Google Cloud Datastore vs. GridGain

System Properties Comparison AnzoGraph DB vs. Cloudflare Workers KV vs. Google Cloud Datastore vs. GridGain

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelGraph DBMS
RDF store
Key-value storeDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.32
Rank#283  Overall
#40  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.cloudflare.com/­developer-platform/­workers-kvcloud.google.com/­datastorewww.gridgain.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.html
DeveloperCambridge SemanticsCloudflareGoogleGridGain Systems, Inc.
Initial release2018201820082007
Current release2.3, January 2021GridGain 8.5.1
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 languageJava, C++, .Net
Server operating systemsLinuxhostedhostedLinux
OS X
Solaris
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details hereyes
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.nononoyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
HTTP REST
Proprietary protocol
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC++
Java
Python
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnousing Google App Engineyes (compute grid and cache interceptors can be used instead)
TriggersnonoCallbacks using the Google Apps Engineyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusteryesMulti-source replication using Paxosyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual 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 integrityno infonot needed in graphsnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesnonoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
AnzoGraph DBCloudflare Workers KVGoogle Cloud DatastoreGridGain
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