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DBMS > Apache Druid vs. InfinityDB vs. Riak KV vs. Sqrrl

System Properties Comparison Apache Druid vs. InfinityDB vs. Riak KV vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonInfinityDB  Xexclude from comparisonRiak KV  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA Java embedded Key-Value Store which extends the Java Map interfaceDistributed, fault tolerant key-value storeAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score0.00
Rank#383  Overall
#59  Key-value stores
Score3.84
Rank#76  Overall
#9  Key-value stores
Websitedruid.apache.orgboilerbay.comsqrrl.com
Technical documentationdruid.apache.org/­docs/­latest/­designboilerbay.com/­infinitydb/­manualwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation and contributorsBoiler Bay Inc.OpenSource, formerly Basho TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release2012200220092012
Current release30.0.0, June 20244.03.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen 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 languageJavaJavaErlangJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Linux
Data schemeyes infoschema-less columns are supportedyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysnoyes
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
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityrestrictedyes
SQL infoSupport of SQLSQL for queryingnonono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
Native Erlang Interface
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
JavaC 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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnonoErlangno
Triggersnonoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding infono "single point of failure"Sharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneselectable replication factorselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoOptimistic locking for transactions; no isolation for bulk loadsnoAtomic updates per row, document, or graph entity
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.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoyes, using Riak SecurityCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache DruidInfinityDBRiak KVSqrrl
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