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DBMS > Apache Druid vs. Google BigQuery vs. Linter vs. YugabyteDB

System Properties Comparison Apache Druid vs. Google BigQuery vs. Linter vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonLinter  Xexclude from comparisonYugabyteDB  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 tablesRDBMS for high security requirementsHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score0.10
Rank#350  Overall
#153  Relational DBMS
Score3.11
Rank#99  Overall
#51  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­bigquerylinter.ruwww.yugabyte.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigquery/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software Foundation and contributorsGooglerelex.ruYugabyte Inc.
Initial release2012201019902017
Current release29.0.1, April 20242.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageJavaC and C++C and C++
Server operating systemsLinux
OS X
Unix
hostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Data schemeyes infoschema-less columns are supportedyesyesdepending on used data model
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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL for queryingyesyesyes, PostgreSQL compatible
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP/JSON APIADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptyes infoproprietary syntax with the possibility to convert from PL/SQLyes infosql, plpgsql, C
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednonenoneHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoSince BigQuery is designed for querying dataACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
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)fine grained access rights according to SQL-standardyes
More information provided by the system vendor
Apache DruidGoogle BigQueryLinterYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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More resources
Apache DruidGoogle BigQueryLinterYugabyteDB
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