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DBMS > Apache Druid vs. CockroachDB vs. HarperDB vs. HBase vs. Quasardb

System Properties Comparison Apache Druid vs. CockroachDB vs. HarperDB vs. HBase vs. Quasardb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCockroachDB  Xexclude from comparisonHarperDB  Xexclude from comparisonHBase  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Wide-column store based on Apache Hadoop and on concepts of BigTableDistributed, high-performance timeseries database
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument storeWide column storeTime Series 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
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitedruid.apache.orgwww.cockroachlabs.comwww.harperdb.iohbase.apache.orgquasar.ai
Technical documentationdruid.apache.org/­docs/­latest/­designwww.cockroachlabs.com/­docsdocs.harperdb.io/­docshbase.apache.org/­book.htmldoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsCockroach LabsHarperDBApache Software Foundation infoApache top-level project, originally developed by Powersetquasardb
Initial release20122015201720082009
Current release29.0.1, April 202423.1.1, May 20233.1, August 20212.3.4, January 20213.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0, commercial license availablecommercial infofree community edition availableOpen Source infoApache version 2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoNode.jsJavaC++
Server operating systemsLinux
OS X
Unix
Linux
macOS
Windows
Linux
OS X
Linux
Unix
Windows infousing Cygwin
BSD
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supporteddynamic schemadynamic schemaschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesoptions to bring your own types, AVROyes infointeger and binary
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.nonononono
Secondary indexesyesyesyesnoyes infowith tags
SQL infoSupport of SQLSQL for queryingyes, wire compatible with PostgreSQLSQL-like data manipulation statementsnoSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
RESTful HTTP API
Thrift
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnonoCustom Functions infosince release 3.1yes infoCoprocessors in Javano
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using RAFTyes infothe nodes on which a table resides can be definedMulti-source replication
Source-replica replication
Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyeswith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of specific operationsSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes infoTransient mode
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlAccess rights for users and rolesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACCryptographically strong user authentication and audit trail

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More resources
Apache DruidCockroachDBHarperDBHBaseQuasardb
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