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DBMS > Apache Druid vs. GigaSpaces vs. Spark SQL vs. Teradata Aster vs. Valentina Server

System Properties Comparison Apache Druid vs. GigaSpaces vs. Spark SQL vs. Teradata Aster vs. Valentina Server

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonValentina Server  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 dataHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and typesObject-relational database and reports server
Primary database modelRelational DBMS
Time Series DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitedruid.apache.orgwww.gigaspaces.comspark.apache.org/­sqlwww.valentina-db.net
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation and contributorsGigaspaces TechnologiesApache Software FoundationTeradataParadigma Software
Initial release20122000201420051999
Current release29.0.1, April 202415.5, September 20203.5.0 ( 2.13), September 20235.7.5
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetScala
Server operating systemsLinux
OS X
Unix
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesFlexible 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 dateyesyesyesyesyes
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.nono infoXML can be used for describing objects metadatanoyes infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL for queryingSQL-99 for query and DML statementsSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C++
Java
Python
Scala
Java
Python
R
Scala
C
C#
C++
Java
Python
R
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoyesnoR packagesyes
Triggersnoyes, event driven architecturenonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
noneyes 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 methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache DruidGigaSpacesSpark SQLTeradata AsterValentina Server
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