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DBMS > Google Cloud Spanner vs. Ignite vs. Kdb vs. SiteWhere

System Properties Comparison Google Cloud Spanner vs. Ignite vs. Kdb vs. SiteWhere

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonIgnite  Xexclude from comparisonKdb  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionA 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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.High performance Time Series DBMSM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
Vector DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitecloud.google.com/­spannerignite.apache.orgkx.comgithub.com/­sitewhere/­sitewhere
Technical documentationcloud.google.com/­spanner/­docsapacheignite.readme.io/­docscode.kx.comsitewhere1.sitewhere.io/­index.html
DeveloperGoogleApache Software FoundationKx Systems, a division of First Derivatives plcSiteWhere
Initial release201720152000 infokdb was released 2000, kdb+ in 20032010
Current releaseApache Ignite 2.63.6, May 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree 32-bit versionOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetqJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyespredefined scheme
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesyesno
Secondary indexesyesyesyes infotable attribute 'grouped'no
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011ANSI-99 for query and DML statements, subset of DDLSQL-like query language (q)no
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
HTTP REST
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersnoyes (cache interceptors and events)yes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yes (replicated cache)Source-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDnono
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsrights management via user accountsUsers with fine-grained authorization concept
More information provided by the system vendor
Google Cloud SpannerIgniteKdbSiteWhere
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
Google Cloud SpannerIgniteKdbSiteWhere
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