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DBMS > Amazon Aurora vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. RavenDB

System Properties Comparison Amazon Aurora vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. RavenDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonDistributed 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.Open Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Document store
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.92
Rank#101  Overall
#18  Document stores
Websiteaws.amazon.com/­rds/­auroradgraph.iowww.esgyn.cncloud.google.com/­bigtableravendb.net
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldgraph.io/­docscloud.google.com/­bigtable/­docsravendb.net/­docs
DeveloperAmazonDgraph Labs, Inc.EsgynGoogleHibernating Rhinos
Initial release20152016201520152010
Current release5.4, July 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC#
Server operating systemshostedLinux
OS X
Windows
LinuxhostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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.yesnonono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoyesnoSQL-like query language (RQL)
APIs and other access methodsADO.NET
JDBC
ODBC
GraphQL 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)
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoJava Stored Proceduresnoyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardno 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)Authorization levels configured per client per database

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More resources
Amazon AuroraDgraphEsgynDBGoogle Cloud BigtableRavenDB
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