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DBMS > etcd vs. Microsoft Azure Table Storage vs. Solr vs. Sqrrl

System Properties Comparison etcd vs. Microsoft Azure Table Storage vs. Solr vs. Sqrrl

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA distributed reliable key-value storeA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeWide column storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.64
Rank#54  Overall
#5  Key-value stores
Score4.92
Rank#73  Overall
#6  Wide column stores
Score44.28
Rank#24  Overall
#3  Search engines
Websiteetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.orgsqrrl.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
solr.apache.org/­resources.html
DeveloperMicrosoftApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release201220062012
Current release3.4, August 20199.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or datenoyesyes 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.nonoyes
Secondary indexesnonoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceno
APIs and other access methodsgRPC
JSON over HTTP
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
C++
Java
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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnonoJava pluginsno
Triggersyes, watching key changesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingoptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
etcdMicrosoft Azure Table StorageSolrSqrrl
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