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DBMS > Amazon Aurora vs. Databricks vs. InfluxDB vs. Oracle Berkeley DB

System Properties Comparison Amazon Aurora vs. Databricks vs. InfluxDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabricks  Xexclude from comparisonInfluxDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.DBMS for storing time series, events and metricsWidely used in-process key-value store
Primary database modelRelational DBMSDocument store
Relational DBMS
Time Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument storeSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteaws.amazon.com/­rds/­aurorawww.databricks.comwww.influxdata.com/­products/­influxdb-overviewwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databricks.comdocs.influxdata.com/­influxdbdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAmazonDatabricksOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2015201320131994
Current release2.7.6, April 202418.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedLinux
OS X infothrough Homebrew
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesNumeric data and Stringsno
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.yesyesnoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyeswith Databricks SQLSQL-like query languageyes infoSQL interfaced based on SQLite is available
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
HTTP API
JSON over UDP
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Python
R
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.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 proceduresyesuser defined functions and aggregatesnono
Triggersyesnoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoin enterprise version onlynone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesselectable replication factor infoin enterprise version onlySource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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.yesnoyes infoDepending on used storage engineyes
User concepts infoAccess controlfine grained access rights according to SQL-standardsimple rights management via user accountsno
More information provided by the system vendor
Amazon AuroraDatabricksInfluxDBOracle Berkeley DB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
InfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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More resources
Amazon AuroraDatabricksInfluxDBOracle Berkeley DB
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