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DBMS > Datomic vs. etcd vs. SAP SQL Anywhere vs. Solr vs. Spark SQL

System Properties Comparison Datomic vs. etcd vs. SAP SQL Anywhere vs. Solr vs. Spark SQL

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonetcd  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  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 durabilityA distributed reliable key-value storeRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsA 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 DBMSKey-value storeRelational 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.25
Rank#79  Overall
#43  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.cometcd.io
github.com/­etcd-io/­etcd
www.sap.com/­products/­technology-platform/­sql-anywhere.htmlsolr.apache.orgspark.apache.org/­sql
Technical documentationdocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
help.sap.com/­docs/­SAP_SQL_Anywheresolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectSAP infoformerly SybaseApache Software FoundationApache Software Foundation
Initial release2012199220062014
Current release1.0.6735, June 20233.4, August 201917, July 20159.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureGoJavaScala
Server operating systemsAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
AIX
HP-UX
Linux
OS X
Solaris
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 schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesnoyesyes 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.nonoyesyesno
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnonoyesSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIgRPC
JSON over HTTP
ADO.NET
HTTP API
JDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
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 Functionsnoyes, in C/C++, Java, .Net or PerlJava pluginsno
TriggersBy using transaction functionsyes, watching key changesyesyes 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 peersnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Source-replica replication infoDatabase mirroringyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentnoyesyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standardyesno

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More resources
DatomicetcdSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSolrSpark SQL
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