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DBMS > Apache Druid vs. BigchainDB vs. GigaSpaces vs. Spark SQL vs. Teradata Aster

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

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigchainDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSpark SQL  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 dataBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsHigh 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 types
Primary database modelRelational DBMS
Time Series DBMS
Document storeDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.79
Rank#212  Overall
#36  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgwww.bigchaindb.comwww.gigaspaces.comspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designbigchaindb.readthedocs.io/­en/­latestdocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsGigaspaces TechnologiesApache Software FoundationTeradata
Initial release20122016200020142005
Current release29.0.1, April 202415.5, September 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL v3Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonJava, C++, .NetScala
Server operating systemsLinux
OS X
Unix
LinuxLinux
macOS
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyesFlexible 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 dateyesnoyesyesyes
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 metadatanoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingnoSQL-99 for query and DML statementsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
CLI Client
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
C++
Java
Python
Scala
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesnoR packages
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorMulti-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 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 Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesRole-based access controlnofine grained access rights according to SQL-standard

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More resources
Apache DruidBigchainDBGigaSpacesSpark SQLTeradata Aster
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