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DBMS > Amazon Aurora vs. Apache IoTDB vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed 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.
Primary database modelRelational DBMSTime Series DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series 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
Websiteaws.amazon.com/­rds/­auroraiotdb.apache.orgdgraph.iowww.esgyn.cncloud.google.com/­bigtable
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldgraph.io/­docscloud.google.com/­bigtable/­docs
DeveloperAmazonApache Software FoundationDgraph Labs, Inc.EsgynGoogle
Initial release20152018201620152015
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++, Java
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linuxhosted
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.yesnononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like query languagenoyesno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native API
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)
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#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyesnoJava Stored Proceduresno
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDAtomic single-row operations
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.yesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardyesno 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)

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More resources
Amazon AuroraApache IoTDBDgraphEsgynDBGoogle Cloud Bigtable
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