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DBMS > Apache Druid vs. Coveo vs. GigaSpaces vs. Teradata Aster

System Properties Comparison Apache Druid vs. Coveo vs. GigaSpaces vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCoveo  Xexclude from comparisonGigaSpaces  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Search engineDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score2.34
Rank#117  Overall
#11  Search engines
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Websitedruid.apache.orgwww.coveo.comwww.gigaspaces.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.coveo.comdocs.gigaspaces.com/­latest/­landing.html
DeveloperApache Software Foundation and contributorsCoveoGigaspaces TechnologiesTeradata
Initial release2012201220002005
Current release29.0.1, April 202415.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
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 languageJavaJava, C++, .Net
Server operating systemsLinux
OS X
Unix
hostedLinux
macOS
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedhybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono infoXML can be used for describing objects metadatayes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoSQL-99 for query and DML statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
Java
JavaScript
Python
.Net
C++
Java
Python
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyesR packages
Triggersnoyesyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID
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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemgranular access controls, API key management, content filtersRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache DruidCoveoGigaSpacesTeradata Aster
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