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DBMS > etcd vs. Solr vs. Spark SQL vs. Titan

System Properties Comparison etcd vs. Solr vs. Spark SQL vs. Titan

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionA distributed reliable key-value storeA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelKey-value storeSearch engineRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
solr.apache.orgspark.apache.org/­sqlgithub.com/­thinkaurelius/­titan
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
solr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software FoundationApache Software FoundationAurelius, owned by DataStax
Initial release200620142012
Current release3.4, August 20199.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaScalaJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or datenoyes infosupports customizable data types and automatic typingyesyes
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.noyesno
Secondary indexesnoyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceSQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresnoJava pluginsnoyes
Triggersyes, watching key changesyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Coreyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoyesnoUser authentification and security via Rexster Graph Server

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More resources
etcdSolrSpark SQLTitan
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