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DBMS > Hive vs. Ignite vs. Riak TS vs. Sqrrl

System Properties Comparison Hive vs. Ignite vs. Riak TS vs. Sqrrl

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIgnite  Xexclude from comparisonRiak TS  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.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KVAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websitehive.apache.orgignite.apache.orgsqrrl.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationOpen Source, formerly Basho TechnologiesAmazon infooriginally Sqrrl Data, Inc.
Initial release2012201520152012
Current release3.1.3, April 2022Apache Ignite 2.63.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetErlangJava
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
OS X
Linux
Data schemeyesyesschema-freeschema-free
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.yesno
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLyes, limitedno
APIs and other access methodsJDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)Erlangno
Triggersnoyes (cache interceptors and events)yes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)selectable replication factorselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)yesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoAtomic 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.yes
User concepts infoAccess controlAccess rights for users, groups and rolesSecurity Hooks for custom implementationsnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
HiveIgniteRiak TSSqrrl
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