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DBMS > Apache Druid vs. Datomic vs. Riak KV vs. Teradata Aster

System Properties Comparison Apache Druid vs. Datomic vs. Riak KV vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonRiak KV  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 dataDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed, fault tolerant key-value storePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitedruid.apache.orgwww.datomic.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation and contributorsCognitectOpenSource, formerly Basho TechnologiesTeradata
Initial release2012201220092005
Current release29.0.1, April 20241.0.7075, December 20233.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freeOpen Source infoApache version 2, commercial enterprise editioncommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureErlang
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Linux
Data schemeyes infoschema-less columns are supportedyesschema-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 dateyesyesnoyes
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.nononoyes infoin Aster File Store
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLSQL for queryingnonoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIHTTP API
Native Erlang Interface
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsErlangR packages
TriggersnoBy using transaction functionsyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersselectable replication factoryes 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 methodsnonoyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
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 persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoyes, using Riak Securityfine grained access rights according to SQL-standard

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More resources
Apache DruidDatomicRiak KVTeradata Aster
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