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DBMS > Apache Drill vs. Atos Standard Common Repository vs. IRONdb vs. RRDtool vs. Spark SQL

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. IRONdb vs. RRDtool vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonIRONdb  Xexclude from comparisonRRDtool  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Time Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedrill.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.circonus.com/solutions/time-series-database/oss.oetiker.ch/­rrdtoolspark.apache.org/­sql
Technical documentationdrill.apache.org/­docsdocs.circonus.com/irondb/category/getting-startedoss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationAtos Convergence CreatorsCirconus LLC.Tobias OetikerApache Software Foundation
Initial release20122016201719992014
Current release1.20.3, January 20231703V0.10.20, January 20181.8.0, 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoGPL V2 and FLOSSOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C infoImplementations in Java (e.g. RRD4J) and C# availableScala
Server operating systemsLinux
OS X
Windows
LinuxLinuxHP-UX
Linux
Linux
OS X
Windows
Data schemeschema-freeSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptionalyes infotext, numeric, histogramsNumeric data onlyyes
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.noyesnono infoExporting into and restoring from XML files possibleno
Secondary indexesnoyesnonono
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
LDAPHTTP APIin-process shared library
Pipes
JDBC
ODBC
Supported programming languagesC++All languages with LDAP bindings.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes, in Luanono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionAutomatic, metric affinity per nodenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency per node, eventual consistency across nodesnone
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoby using the rrdcached daemonyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesnoyesno
User concepts infoAccess controlDepending on the underlying data sourceLDAP bind authenticationnonono

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More resources
Apache DrillAtos Standard Common RepositoryIRONdbRRDtoolSpark SQL
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