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DBMS > EsgynDB vs. FoundationDB vs. Google Cloud Bigtable vs. HugeGraph

System Properties Comparison EsgynDB vs. FoundationDB vs. Google Cloud Bigtable vs. HugeGraph

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonGoogle Cloud Bigtable  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOrdered key-value store. Core features are complimented by layers.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value store
Wide column store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitewww.esgyn.cngithub.com/­apple/­foundationdbcloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
Technical documentationapple.github.io/­foundationdbcloud.google.com/­bigtable/­docshugegraph.apache.org/­docs
DeveloperEsgynFoundationDBGoogleBaidu
Initial release2015201320152018
Current release6.2.28, November 20200.9
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC++Java
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
macOS
Unix
Data schemeyesschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingnoyes
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 indexesyesnonoyes infoalso supports composite index and range index
SQL infoSupport of SQLyessupported in specific SQL layer onlynono
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresJava Stored Proceduresin SQL-layer onlynoasynchronous Gremlin script jobs
Triggersnononono
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 nodesMulti-source replication between multi datacentersyesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesin SQL-layer onlynoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions

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More resources
EsgynDBFoundationDBGoogle Cloud BigtableHugeGraph
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