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DBMS > Apache Druid vs. Drizzle vs. EXASOL vs. Google Cloud Bigtable vs. STSdb

System Properties Comparison Apache Druid vs. Drizzle vs. EXASOL vs. Google Cloud Bigtable vs. STSdb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDrizzle  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSTSdb  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSKey-value store
Wide column store
Key-value 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
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitedruid.apache.orgwww.exasol.comcloud.google.com/­bigtablegithub.com/­STSSoft/­STSdb4
Technical documentationdruid.apache.org/­docs/­latest/­designwww.exasol.com/­resourcescloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation and contributorsDrizzle project, originally started by Brian AkerExasolGoogleSTS Soft SC
Initial release20122008200020152011
Current release29.0.1, April 20247.2.4, September 20124.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGNU GPLcommercialcommercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
OS X
hostedWindows
Data schemeyes infoschema-less columns are supportedyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes infoprimitive types and user defined types (classes)
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.nonono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL for queryingyes infowith proprietary extensionsyesnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Java
PHP
Java
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
Server-side scripts infoStored proceduresnonouser defined functionsnono
Triggersnono infohooks for callbacks inside the server can be used.yesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operationsno
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache DruidDrizzleEXASOLGoogle Cloud BigtableSTSdb
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