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DBMS > Apache Druid vs. Badger vs. Faircom EDGE vs. IBM Db2 Event Store vs. Rockset

System Properties Comparison Apache Druid vs. Badger vs. Faircom EDGE vs. IBM Db2 Event Store vs. Rockset

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBadger  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsDistributed Event Store optimized for Internet of Things use casesA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-value store
Relational DBMS
Event Store
Time Series DBMS
Document store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitedruid.apache.orggithub.com/­dgraph-io/­badgerwww.faircom.com/­products/­faircom-edgewww.ibm.com/­products/­db2-event-storerockset.com
Technical documentationdruid.apache.org/­docs/­latest/­designgodoc.org/­github.com/­dgraph-io/­badgerdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.ibm.com/­docs/­en/­db2-event-storedocs.rockset.com
DeveloperApache Software Foundation and contributorsDGraph LabsFairCom CorporationIBMRockset
Initial release20122017197920172019
Current release29.0.1, April 2024V3, October 20202.0
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercial infoRestricted, free version availablecommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoANSI C, C++C and C++C++
Server operating systemsLinux
OS X
Unix
BSD
Linux
OS X
Solaris
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux infoLinux, macOS, Windows for the developer additionhosted
Data schemeyes infoschema-less columns are supportedschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesnoyes, ANSI Standard SQL Typesyesdynamic typing
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.nonoyesnono infoingestion from XML files supported
Secondary indexesyesnoyesnoall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnoyes infoANSI SQL queriesyes infothrough the embedded Spark runtimeRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
GoC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++yesno
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneFile partitioning infoCustomizable business rules for partitioningShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsActive-active shard replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Tunable Consistency
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standardAccess rights for users and organizations can be defined via Rockset console

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More resources
Apache DruidBadgerFaircom EDGE infoformerly c-treeEDGEIBM Db2 Event StoreRockset
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