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

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparisonTigerGraph  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 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 AccumuloA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelWide column storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.77
Rank#66  Overall
#5  Wide column stores
Score51.62
Rank#20  Overall
#3  Search engines
Score1.13
Rank#159  Overall
#12  Graph DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableslucene.apache.org/­solrsqrrl.comwww.tigergraph.com
Technical documentationlucene.apache.org/­solr/­resources.htmldocs.tigergraph.com
DeveloperMicrosoftApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2012200620122017
Current release8.6.2, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxLinux
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-freeyes
Typing infopredefined data types such as float or dateyesyes 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 indexedyes
SQL infoSupport of SQLnoSolr Parallel SQL InterfacenoSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.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
C++
Java
Server-side scripts infoStored proceduresnoJava pluginsnoyes
Triggersnoyes infoUser configurable commands triggered on index changesnono
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 nodesyes 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 methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyesyes
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 integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingoptimistic lockingAtomic updates per row, document, or graph entityACID
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.noyesno
User concepts infoAccess controlAccess 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)Role-based access control
More information provided by the system vendor
Microsoft Azure Table StorageSolrSqrrlTigerGraph
Specific characteristicsTigerGraph is a native graph database, with massively parallel processing and fully...
» more
Competitive advantagesTigerGraph is the fastest and most scalable graph platform, powered by a native parallel...
» more
Typical application scenariosAnti Money Laundering Real-Time Fraud Detection Customer 360 Real-Time Personalized...
» more
Key customersTigerGraph’s proven technology supports applications such as fraud detection, customer...
» more
Market metricsTigerGraph is 2x to more than 8000x faster at graph traversal and query response...
» more
Licensing and pricing modelsNEW: TIGERGRAPH CLOUD - Fully managed Graph Database as a Service. Hourly pricing...
» more

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Microsoft Azure Table StorageSolrSqrrlTigerGraph
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