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DBMS > Drizzle vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. Spark SQL

System Properties Comparison Drizzle vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. Spark SQL

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonSpark SQL  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.High performance Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablekx.comspark.apache.org/­sql
Technical documentationcloud.google.com/­bigtable/­docscode.kx.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerEsgynGoogleKx Systems, a division of First Derivatives plcApache Software Foundation
Initial release2008201520152000 infokdb was released 2000, kdb+ in 20032014
Current release7.2.4, September 20123.6, May 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial infofree 32-bit versionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaqScala
Server operating systemsFreeBSD
Linux
OS X
LinuxhostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nonoyesno
Secondary indexesyesyesnoyes infotable attribute 'grouped'no
SQL infoSupport of SQLyes infowith proprietary extensionsyesnoSQL-like query language (q)SQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnouser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.nonoyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsnono
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsno
More information provided by the system vendor
DrizzleEsgynDBGoogle Cloud BigtableKdbSpark SQL
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
DrizzleEsgynDBGoogle Cloud BigtableKdbSpark SQL
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