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DBMS > GigaSpaces vs. Solr vs. Teradata Aster vs. WakandaDB

System Properties Comparison GigaSpaces vs. Solr vs. Teradata Aster vs. WakandaDB

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonSolr  Xexclude from comparisonTeradata Aster  Xexclude from comparisonWakandaDB  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA widely used distributed, scalable search engine based on Apache LucenePlatform for big data analytics on multistructured data sources and typesWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Search engineRelational DBMSObject oriented DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.gigaspaces.comsolr.apache.orgwakanda.github.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlsolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperGigaspaces TechnologiesApache Software FoundationTeradataWakanda SAS
Initial release2000200620052012
Current release15.5, September 20209.6.1, May 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache Version 2commercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaC++, JavaScript
Server operating systemsLinux
macOS
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxLinux
OS X
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
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.no infoXML can be used for describing objects metadatayesyes infoin Aster File Storeno
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSolr Parallel SQL Interfaceyesno
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
RESTful HTTP API
Supported programming languages.Net
C++
Java
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
JavaScript
Server-side scripts infoStored proceduresyesJava pluginsR packagesyes
Triggersyes, event driven architectureyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACIDACID
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.yesyesnono
User concepts infoAccess controlRole-based access controlyesfine grained access rights according to SQL-standardyes

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More resources
GigaSpacesSolrTeradata AsterWakandaDB
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