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DBMS > FoundationDB vs. Google Cloud Datastore vs. HBase vs. HugeGraph

System Properties Comparison FoundationDB vs. Google Cloud Datastore vs. HBase vs. HugeGraph

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonHugeGraph  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTableA fast-speed and highly-scalable Graph DBMS
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document storeWide column storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitegithub.com/­apple/­foundationdbcloud.google.com/­datastorehbase.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationapple.github.io/­foundationdbcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlhugegraph.apache.org/­docs
DeveloperFoundationDBGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetBaidu
Initial release2013200820082018
Current release6.2.28, November 20202.3.4, January 20210.9
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsLinux
OS X
Windows
hostedLinux
Unix
Windows infousing Cygwin
Linux
macOS
Unix
Data schemeschema-free infosome layers support schemasschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateno infosome layers support typingyes, details hereoptions to bring your own types, AVROyes
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.nonono
Secondary indexesnoyesnoyes infoalso supports composite index and range index
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query language (GQL)nono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Groovy
Java
Python
Server-side scripts infoStored proceduresin SQL-layer onlyusing Google App Engineyes infoCoprocessors in Javaasynchronous Gremlin script jobs
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable 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 or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityin SQL-layer onlyyes infovia ReferenceProperties or Ancestor pathsnoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)ACID
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.noyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUsers, roles and permissions

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FoundationDBGoogle Cloud DatastoreHBaseHugeGraph
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