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DBMS > Apache Druid vs. Atos Standard Common Repository vs. Badger vs. Faircom DB vs. Tkrzw

System Properties Comparison Apache Druid vs. Atos Standard Common Repository vs. Badger vs. Faircom DB vs. Tkrzw

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBadger  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
This system has been discontinued and 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 dataHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMS
Time Series DBMS
Document store
Key-value store
Key-value storeKey-value store
Relational DBMS
Key-value store
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
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitedruid.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­dgraph-io/­badgerwww.faircom.com/­products/­faircom-dbdbmx.net/­tkrzw
Technical documentationdruid.apache.org/­docs/­latest/­designgodoc.org/­github.com/­dgraph-io/­badgerdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation and contributorsAtos Convergence CreatorsDGraph LabsFairCom CorporationMikio Hirabayashi
Initial release20122016201719792020
Current release29.0.1, April 20241703V12, November 20200.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaGoANSI C, C++C++
Server operating systemsLinux
OS X
Unix
LinuxBSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Data schemeyes infoschema-less columns are supportedSchema and schema-less with LDAP viewsschema-freeschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesoptionalnoyes, ANSI SQL Types, JSON, typed binary structuresno
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.noyesnonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingnonoyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
LDAPADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages with LDAP bindingsGo.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononoyes info.Net, JavaScript, C/C++no
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infocell divisionnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnotunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesyes infousing specific database classes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemLDAP bind authenticationnoFine grained access rights according to SQL-standard with additional protections for filesno

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More resources
Apache DruidAtos Standard Common RepositoryBadgerFaircom DB infoformerly c-treeACETkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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