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DBMS > Dgraph vs. EsgynDB vs. Faircom DB vs. Google Cloud Bigtable

System Properties Comparison Dgraph vs. EsgynDB vs. Faircom DB vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelGraph DBMSRelational DBMSKey-value store
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.71
Rank#131  Overall
#11  Graph DBMS
Score0.26
Rank#274  Overall
#127  Relational DBMS
Score0.43
Rank#247  Overall
#38  Key-value stores
#116  Relational DBMS
Score3.58
Rank#88  Overall
#7  Wide column stores
Websitedgraph.iowww.esgyn.cnwww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtable
Technical documentationdgraph.io/­docslearn.faircomcorp.com/­developers/­documentation_directorycloud.google.com/­bigtable/­docs
DeveloperDgraph Labs, Inc.EsgynFairCom CorporationGoogle
Initial release2016201519792015
Current releaseV12, November 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaANSI C, C++
Server operating systemsLinux
OS X
Windows
LinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hosted
Data schemeschema-freeyesschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresno
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 indexesyesyesyesno
SQL infoSupport of SQLnoyesyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes info.Net, JavaScript, C/C++no
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesyesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDtunable from ACID to Eventually ConsistentAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
DgraphEsgynDBFaircom DB infoformerly c-treeACEGoogle Cloud Bigtable
Specific characteristicsAchieve Hundreds of Thousands of Transactions Per Second on A Single Database Server...
» more
Competitive advantagesHorizontally scalable transactional graph database with fast arbitrary-depth joins...
» more
Top Features SQL Key-value store and navigational NoSQL API Indexed binary objects...
» more
Typical application scenariosReal-time transaction processing solutions leverage FairCom DB because its NoSQL...
» more
Key customersMicrosoft, UPS, Verizon, Motorola, Commvault, Thomson Reuters, ACI, BNY Mellon, Rockwell...
» more
Market metricsFrom banking and financial transactions, transportation, warehouse automation, package...
» more
Licensing and pricing modelsJust as the technical aspects of FairCom DB are flexible to meet operation requirements,...
» more

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More resources
DgraphEsgynDBFaircom DB infoformerly c-treeACEGoogle Cloud Bigtable
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