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DBMS > Apache Druid vs. Google BigQuery vs. Hazelcast vs. Linter vs. Trafodion

System Properties Comparison Apache Druid vs. Google BigQuery vs. Hazelcast vs. Linter vs. Trafodion

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonTrafodion  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataLarge scale data warehouse service with append-only tablesA widely adopted in-memory data gridRDBMS for high security requirementsTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.39
Rank#124  Overall
#61  Relational DBMS
#8  Time Series DBMS
Score54.13
Rank#22  Overall
#15  Relational DBMS
Score9.60
Rank#50  Overall
#5  Key-value stores
Score0.13
Rank#351  Overall
#149  Relational DBMS
Score0.72
Rank#237  Overall
#113  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­bigqueryhazelcast.comlinter.ru/­entrafodion.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigquery/­docshazelcast.org/­imdg/­docstrafodion.apache.org
DeveloperApache Software Foundation and contributorsGoogleHazelcastrelex.ru/­enApache Software Foundation, originally developed by HP
Initial release20122010200819902014
Current release24.0.0, September 20225.2.1, November 20222.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++C++, Java
Server operating systemsLinux
OS X
Unix
hostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infothe object must implement a serialization strategynono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL for queryingyesSQL-like query languageyesyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLJava Stored Procedures
Triggersnonoyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoReplicated MapSource-replica replicationyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying dataone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache DruidGoogle BigQueryHazelcastLinterTrafodion
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