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DBMS > Apache Druid vs. Brytlyt vs. Google Cloud Spanner vs. HBase

System Properties Comparison Apache Druid vs. Brytlyt vs. Google Cloud Spanner vs. HBase

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA 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.Wide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSWide column store
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
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitedruid.apache.orgbrytlyt.iocloud.google.com/­spannerhbase.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.brytlyt.iocloud.google.com/­spanner/­docshbase.apache.org/­book.html
DeveloperApache Software Foundation and contributorsBrytlytGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2012201620172008
Current release29.0.1, April 20245.0, August 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAJava
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedLinux
Unix
Windows infousing Cygwin
Data schemeyes infoschema-less columns are supportedyesyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVRO
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingyesyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLnoyes infoCoprocessors in Java
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynoyesyes 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 isolationSingle row ACID (across millions of columns)
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.nonoyes
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-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
Apache DruidBrytlytGoogle Cloud SpannerHBase
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