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DBMS > Datomic vs. NuoDB vs. Solr vs. Spark SQL

System Properties Comparison Datomic vs. NuoDB vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonNuoDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNuoDB is a webscale distributed database that supports SQL and ACID transactionsA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.89
Rank#198  Overall
#92  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comwww.3ds.com/­nuodb-distributed-sql-databasesolr.apache.orgspark.apache.org/­sql
Technical documentationdocs.datomic.comdoc.nuodb.comsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectDassault Systèmes infooriginally NuoDB, Inc.Apache Software FoundationApache Software Foundation
Initial release2012201320062014
Current release1.0.6735, June 20239.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infolimited edition freeOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++JavaScala
Server operating systemsAll OS with a Java VMhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.nonoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoyesSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava, SQLJava pluginsno
TriggersBy using transaction functionsyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersdata is dynamically stored/cached on the nodes where it is read/writtenShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoManaged transparently by NuoDByesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infotunable commit protocoloptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes infoTemporary tableyesno
User concepts infoAccess controlnoStandard SQL roles/ privileges, Administrative Usersyesno

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