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DBMS > AnzoGraph DB vs. Google Cloud Datastore vs. Kyligence Enterprise vs. OrigoDB vs. Prometheus

System Properties Comparison AnzoGraph DB vs. Google Cloud Datastore vs. Kyligence Enterprise vs. OrigoDB vs. Prometheus

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonOrigoDB  Xexclude from comparisonPrometheus  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 PlatformA distributed analytics engine for big data, built on top of Apache KylinA fully ACID in-memory object graph databaseOpen-source Time Series DBMS and monitoring system
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMSDocument store
Object oriented DBMS
Time Series 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Websitecambridgesemantics.com/­anzographcloud.google.com/­datastorekyligence.io/­kyligence-enterpriseorigodb.comprometheus.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­datastore/­docsorigodb.com/­docsprometheus.io/­docs
DeveloperCambridge SemanticsGoogleKyligence, Inc.Robert Friberg et al
Initial release2018200820162009 infounder the name LiveDB2015
Current release2.3, January 2021
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialOpen SourceOpen Source infoApache 2.0
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 languageJavaC#Go
Server operating systemsLinuxhostedLinuxLinux
Windows
Linux
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesUser defined using .NET types and collectionsNumeric data only
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 infocan be achieved using .NETno infoImport of XML data possible
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (GQL)ANSI SQL for queries (using Apache Calcite)nono
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
JDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP API
LINQ
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineyesno
TriggersnoCallbacks using the Google Apps Engineyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication using PaxosSource-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infousing Google Cloud Dataflowyesnono
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 Consistencynone
Foreign keys infoReferential integrityno infonot needed in graphsyes infovia ReferenceProperties or Ancestor pathsdepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based authorizationno

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More resources
AnzoGraph DBGoogle Cloud DatastoreKyligence EnterpriseOrigoDBPrometheus
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