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DBMS > Google Cloud Bigtable vs. Kdb vs. RavenDB vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. Kdb vs. RavenDB vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonRavenDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGoogle'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 DBMSOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Document storeSearch engine
Secondary database modelsRelational DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score2.68
Rank#102  Overall
#19  Document stores
Score5.97
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­bigtablekx.comravendb.netsphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docscode.kx.comravendb.net/­docssphinxsearch.com/­docs
DeveloperGoogleKx Systems, a division of First Derivatives plcHibernating RhinosSphinx Technologies Inc.
Initial release20152000 infokdb was released 2000, kdb+ in 200320102001
Current release3.6, May 20185.4, July 20223.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree 32-bit versionOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqC#C++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnono
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
Secondary indexesnoyes infotable attribute 'grouped'yesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (q)SQL-like query language (RQL)SQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functionsyesno
Triggersnoyes infowith viewsyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infosimilar paradigm used for internal processingyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsAuthorization levels configured per client per databaseno
More information provided by the system vendor
Google Cloud BigtableKdbRavenDBSphinx
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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Google Cloud BigtableKdbRavenDBSphinx
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