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DBMS > Apache Druid vs. EsgynDB vs. Netezza vs. Sqrrl

System Properties Comparison Apache Druid vs. EsgynDB vs. Netezza vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionData warehouse and analytics appliance part of IBM PureSystemsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
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
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitedruid.apache.orgwww.esgyn.cnwww.ibm.com/­products/­netezzasqrrl.com
Technical documentationdruid.apache.org/­docs/­latest/­design
DeveloperApache Software Foundation and contributorsEsgynIBMAmazon infooriginally Sqrrl Data, Inc.
Initial release2012201520002012
Current release29.0.1, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaJava
Server operating systemsLinux
OS X
Unix
LinuxLinux infoincluded in applianceLinux
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyesyesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C++
Fortran
Java
Lua
Perl
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoJava Stored Proceduresyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersSource-replica replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic updates per row, document, or graph entity
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.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache DruidEsgynDBNetezza infoAlso called PureData System for Analytics by IBMSqrrl
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