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DBMS > Amazon Aurora vs. Apache IoTDB vs. Badger vs. Oracle Berkeley DB

System Properties Comparison Amazon Aurora vs. Apache IoTDB vs. Badger vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache IoTDB  Xexclude from comparisonBadger  Xexclude from comparisonOracle Berkeley DB  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 FlinkAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Widely used in-process key-value store
Primary database modelRelational DBMSTime Series DBMSKey-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.14
Rank#328  Overall
#48  Key-value stores
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­rds/­auroraiotdb.apache.orggithub.com/­dgraph-io/­badgerwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonApache Software FoundationDGraph LabsOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2015201820171994
Current release1.1.0, April 202318.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.yesnonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query languagenoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native 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#
C++
Go
Java
Python
Scala
Go.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyesyesnono
Triggersyesyesnoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenone
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 replicasnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
none
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnono

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More resources
Amazon AuroraApache IoTDBBadgerOracle Berkeley DB
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