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

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

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMemcached  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle'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 PlatformIn-memory key-value store, originally intended for caching
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Document storeKey-value 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
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score4.49
Rank#79  Overall
#12  Document stores
Score20.74
Rank#32  Overall
#4  Key-value stores
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablecloud.google.com/­datastorewww.memcached.org
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsgithub.com/­memcached/­memcached/­wiki
DeveloperDgraph Labs, Inc.EsgynGoogleGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournal
Initial release20162015201520082003
Current release1.6.25, March 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoBSD license
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC
Server operating systemsLinux
OS X
Windows
LinuxhostedhostedFreeBSD
Linux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes, details hereno
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 indexesyesyesnoyesno
SQL infoSupport of SQLnoyesnoSQL-like query language (GQL)no
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoJava Stored Proceduresnousing Google App Engineno
TriggersnononoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosnone infoRepcached, a Memcached patch, provides this functionallity
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes infousing Google Cloud Dataflowno
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 integritynoyesnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesno
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-standardAccess 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)yes infousing SASL (Simple Authentication and Security Layer) protocol

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More resources
DgraphEsgynDBGoogle Cloud BigtableGoogle Cloud DatastoreMemcached
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