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DBMS > Amazon Aurora vs. Apache Druid vs. Ignite vs. Teradata Aster

System Properties Comparison Amazon Aurora vs. Apache Druid vs. Ignite vs. Teradata Aster

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Druid  Xexclude from comparisonIgnite  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.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websiteaws.amazon.com/­rds/­auroradruid.apache.orgignite.apache.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldruid.apache.org/­docs/­latest/­designapacheignite.readme.io/­docs
DeveloperAmazonApache Software Foundation and contributorsApache Software FoundationTeradata
Initial release2015201220152005
Current release29.0.1, April 2024Apache Ignite 2.6
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, .Net
Server operating systemshostedLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyes infoschema-less columns are supportedyesFlexible 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.yesnoyesyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL for queryingANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)R packages
Triggersyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, via HDFS, S3 or other storage enginesyes (replicated cache)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 (compute grid and hadoop accelerator)yes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
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.yesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache DruidIgniteTeradata Aster
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