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DBMS > Apache Druid vs. etcd vs. Faircom EDGE vs. Vitess

System Properties Comparison Apache Druid vs. etcd vs. Faircom EDGE vs. Vitess

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonetcd  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA distributed reliable key-value storeFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitedruid.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.faircom.com/­products/­faircom-edgevitess.io
Technical documentationdruid.apache.org/­docs/­latest/­designetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlvitess.io/­docs
DeveloperApache Software Foundation and contributorsFairCom CorporationThe Linux Foundation, PlanetScale
Initial release201219792013
Current release29.0.1, April 20243.4, August 2019V3, October 202015.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoANSI C, C++Go
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
Windows infoexperimental
Android
Linux infoARM, x86
Raspbian
Windows
Docker
Linux
macOS
Data schemeyes infoschema-less columns are supportedschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesnoyes, ANSI Standard SQL Typesyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL for queryingnoyes infoANSI SQL queriesyes infowith proprietary extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JSON over HTTP
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++yes infoproprietary syntax
Triggersnoyes, watching key changesyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infowhen using SQLyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes infotable locks or row locks depending on storage engine
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.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.Users with fine-grained authorization concept infono user groups or roles

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More resources
Apache DruidetcdFaircom EDGE infoformerly c-treeEDGEVitess
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