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DBMS > Apache Druid vs. etcd vs. Faircom EDGE vs. Splice Machine

System Properties Comparison Apache Druid vs. etcd vs. Faircom EDGE vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonetcd  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSplice Machine  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 environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeKey-value store
Relational DBMS
Relational 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
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitedruid.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.faircom.com/­products/­faircom-edgesplicemachine.com
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.htmlsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsFairCom CorporationSplice Machine
Initial release201219792014
Current release29.0.1, April 20243.4, August 2019V3, October 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoAGPL 3.0, commercial license 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++Java
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
Windows infoexperimental
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
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
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
JDBC
Native Spark Datasource
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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++yes infoJava
Triggersnoyes, watching key changesyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedFile partitioning infoCustomizable business rules for partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
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 methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)
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.Access rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidetcdFaircom EDGE infoformerly c-treeEDGESplice Machine
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