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DBMS > Amazon SimpleDB vs. Google Cloud Spanner vs. Ignite vs. Solr

System Properties Comparison Amazon SimpleDB vs. Google Cloud Spanner vs. Ignite vs. Solr

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonIgnite  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value storeRelational DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­simpledbcloud.google.com/­spannerignite.apache.orgsolr.apache.org
Technical documentationdocs.aws.amazon.com/­simpledbcloud.google.com/­spanner/­docsapacheignite.readme.io/­docssolr.apache.org/­resources.html
DeveloperAmazonGoogleApache Software FoundationApache Software Foundation
Initial release2007201720152006
Current releaseApache Ignite 2.69.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesyesyes infosupports customizable data types and automatic typing
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.noyesyes
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011ANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interface
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)Java plugins
Triggersnonoyes (cache interceptors and events)yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.yes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACID infoStrict serializable isolationACIDoptimistic locking
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.noyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsyes

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More resources
Amazon SimpleDBGoogle Cloud SpannerIgniteSolr
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