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

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

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Editorial information provided by DB-Engines
NameLovefield  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.
DescriptionEmbeddable relational database for web apps written in pure JavaScriptA 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 modelRelational DBMSWide column storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#248  Overall
#114  Relational DBMS
Score5.81
Rank#66  Overall
#5  Wide column stores
Score52.48
Rank#20  Overall
#3  Search engines
Websitegoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­storage/­tableslucene.apache.org/­solrsqrrl.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdlucene.apache.org/­solr/­resources.html
DeveloperGoogleMicrosoftApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2014201220062012
Current release2.1.12, February 20178.6.2, September 2020
License infoCommercial or Open SourceOpen Source infoApache 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 languageJavaScriptJavaJava
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
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.nonoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternnoSolr Parallel SQL Interfaceno
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesJavaScript.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
TriggersUsing read-only observersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes 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 ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingoptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnoyes
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
LovefieldMicrosoft Azure Table StorageSolrSqrrl
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