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DBMS > Amazon DocumentDB vs. Apache Kylin vs. Solr vs. SQream DB vs. Sqrrl

System Properties Comparison Amazon DocumentDB vs. Apache Kylin vs. Solr vs. SQream DB vs. Sqrrl

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Kylin  Xexclude from comparisonSolr  Xexclude from comparisonSQream DB  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.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA widely used distributed, scalable search engine based on Apache Lucenea GPU-based, columnar RDBMS for big data analytics workloadsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument storeRelational DBMSSearch engineRelational DBMSDocument 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
Score1.91
Rank#131  Overall
#24  Document stores
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websiteaws.amazon.com/­documentdbkylin.apache.orgsolr.apache.orgsqream.comsqrrl.com
Technical documentationaws.amazon.com/­documentdb/­resourceskylin.apache.org/­docssolr.apache.org/­resources.htmldocs.sqream.com
DeveloperApache Software Foundation, originally contributed from eBay IncApache Software FoundationSQream TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release20192015200620172012
Current release3.1.0, July 20209.6.1, May 20242022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, CUDA, Haskell, Java, ScalaJava
Server operating systemshostedLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxLinux
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes, ANSI Standard SQL Typesyes
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 indexesyesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)Solr Parallel SQL Interfaceyesno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
.Net
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoJava pluginsuser defined functions in Pythonno
Triggersnoyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal and vertical partitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsoptimistic lockingACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon DocumentDBApache KylinSolrSQream DBSqrrl
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