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DBMS > Bangdb vs. Drizzle vs. Google Cloud Datastore vs. Kdb

System Properties Comparison Bangdb vs. Drizzle vs. Google Cloud Datastore vs. Kdb

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKdb  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.
DescriptionConverged and high performance database for device data, events, time series, document and graphMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performance Time Series DBMS
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSDocument storeTime Series DBMS
Vector DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitebangdb.comcloud.google.com/­datastorekx.com
Technical documentationdocs.bangdb.comcloud.google.com/­datastore/­docscode.kx.com
DeveloperSachin Sinha, BangDBDrizzle project, originally started by Brian AkerGoogleKx Systems, a division of First Derivatives plc
Initial release2012200820082000 infokdb was released 2000, kdb+ in 2003
Current releaseBangDB 2.0, October 20217.2.4, September 20123.6, May 2018
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoGNU GPLcommercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++q
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes, details hereyes
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.nonoyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes infotable attribute 'grouped'
SQL infoSupport of SQLSQL like support with command line toolyes infowith proprietary extensionsSQL-like query language (GQL)SQL-like query language (q)
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesC
C#
C++
Java
Python
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnonousing Google App Engineuser defined functions
Triggersyes, Notifications (with Streaming only)no infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyes infowith views
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenoyes
User concepts infoAccess controlyes (enterprise version only)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accounts
More information provided by the system vendor
BangdbDrizzleGoogle Cloud DatastoreKdb
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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BangdbDrizzleGoogle Cloud DatastoreKdb
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