DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. OrigoDB vs. PouchDB vs. Spark SQL vs. XTDB

System Properties Comparison Amazon Aurora vs. OrigoDB vs. PouchDB vs. Spark SQL vs. XTDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonOrigoDB  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA fully ACID in-memory object graph databaseJavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processingA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Document storeRelational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.18
Rank#332  Overall
#46  Document stores
Websiteaws.amazon.com/­rds/­auroraorigodb.compouchdb.comspark.apache.org/­sqlgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlorigodb.com/­docspouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.xtdb.com/­docs
DeveloperAmazonRobert Friberg et alApache Software FoundationApache Software FoundationJuxt Ltd.
Initial release20152009 infounder the name LiveDB201220142019
Current release7.1.1, June 20193.5.0 ( 2.13), September 20231.19, September 2021
License infoCommercial or Open SourcecommercialOpen SourceOpen SourceOpen Source infoApache 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaScriptScalaClojure
Server operating systemshostedLinux
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsnoyesyes, extensible-data-notation format
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.yesno infocan be achieved using .NETnonono
Secondary indexesyesyesyes infovia viewsnoyes
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statementslimited SQL, making use of Apache Calcite
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
HTTP API
LINQ
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
HTTP REST
JDBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.NetJavaScriptJava
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresyesyesView functions in JavaScriptnono
Triggersyesyes infoDomain Eventsyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning infoclient side managed; servers are not synchronizedSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesdepending on modelnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole based authorizationnono

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon AuroraOrigoDBPouchDBSpark SQLXTDB infoformerly named Crux
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the news

Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ...
10 June 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ...
14 May 2024, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Knowledge Bases for Amazon Bedrock | Amazon Web Services
2 February 2024, AWS Blog

provided by Google News

Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

provided by Google News

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here