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DBMS > Dgraph vs. EsgynDB vs. Firebird vs. Google Cloud Bigtable vs. Google Cloud Datastore

System Properties Comparison Dgraph vs. EsgynDB vs. Firebird vs. Google Cloud Bigtable vs. Google Cloud Datastore

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebird  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFirebird is an open source RDBMS forked from Borland's InterBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelGraph DBMSRelational DBMSRelational DBMSKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#158  Overall
#15  Graph DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score21.06
Rank#31  Overall
#19  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score4.49
Rank#79  Overall
#12  Document stores
Websitedgraph.iowww.esgyn.cnwww.firebirdsql.orgcloud.google.com/­bigtablecloud.google.com/­datastore
Technical documentationdgraph.io/­docswww.firebirdsql.org/­en/­reference-manualscloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docs
DeveloperDgraph Labs, Inc.EsgynFirebird FoundationGoogleGoogle
Initial release201620152000 infoAs fork of Borland's InterBase20152008
Current release5.0.0, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoInitial Developer's Public Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC and C++
Server operating systemsLinux
OS X
Windows
LinuxAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
hostedhosted
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes, details here
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 indexesyesyesyesnoyes
SQL infoSupport of SQLnoyesyesnoSQL-like query language (GQL)
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoJava Stored ProceduresPSQLnousing Google App Engine
TriggersnonoyesnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesyesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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.
Foreign keys infoReferential integritynoyesyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DgraphEsgynDBFirebirdGoogle Cloud BigtableGoogle Cloud Datastore
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