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DBMS > Apache Druid vs. Apache Phoenix vs. etcd vs. Google BigQuery

System Properties Comparison Apache Druid vs. Apache Phoenix vs. etcd vs. Google BigQuery

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Phoenix  Xexclude from comparisonetcd  Xexclude from comparisonGoogle BigQuery  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed reliable key-value storeLarge scale data warehouse service with append-only tables
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value storeRelational DBMS
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
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score58.10
Rank#19  Overall
#13  Relational DBMS
Websitedruid.apache.orgphoenix.apache.orgetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigquery
Technical documentationdruid.apache.org/­docs/­latest/­designphoenix.apache.orgetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigquery/­docs
DeveloperApache Software Foundation and contributorsApache Software FoundationGoogle
Initial release201220142010
Current release29.0.1, April 20245.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGo
Server operating systemsLinux
OS X
Unix
Linux
Unix
Windows
FreeBSD
Linux
Windows infoexperimental
hosted
Data schemeyes infoschema-less columns are supportedyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL for queryingyesnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCgRPC
JSON over HTTP
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnouser defined functions infoin JavaScript
Triggersnonoyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono infoSince BigQuery is designed for querying data
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)

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More resources
Apache DruidApache PhoenixetcdGoogle BigQuery
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