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DBMS > Apache Druid vs. Bangdb vs. Google Cloud Spanner vs. Quasardb

System Properties Comparison Apache Druid vs. Bangdb vs. Google Cloud Spanner vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBangdb  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataConverged and high performance database for device data, events, time series, document and graphA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Distributed, high-performance timeseries database
Primary database modelRelational DBMS
Time Series DBMS
Document store
Graph DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial 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
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitedruid.apache.orgbangdb.comcloud.google.com/­spannerquasar.ai
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.bangdb.comcloud.google.com/­spanner/­docsdoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsSachin Sinha, BangDBGooglequasardb
Initial release2012201220172009
Current release29.0.1, April 2024BangDB 2.0, October 20213.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoBSD 3commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++
Server operating systemsLinux
OS X
Unix
LinuxhostedBSD
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes 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.nononono
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyes infowith tags
SQL infoSupport of SQLSQL for queryingSQL like support with command line toolyes infoQuery statements complying to ANSI 2011SQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Java
Python
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnononono
Triggersnoyes, Notifications (with Streaming only)nono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication with 3 replicas for regional instances.Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modenoyes infoTransient mode
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes (enterprise version only)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trail

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More resources
Apache DruidBangdbGoogle Cloud SpannerQuasardb
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