DBMS > GeoSpock vs. Google BigQuery vs. Kdb
System Properties Comparison GeoSpock vs. Google BigQuery vs. Kdb
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|Editorial information provided by DB-Engines|
|Name||GeoSpock Xexclude from comparison||Google BigQuery Xexclude from comparison||Kdb Xexclude from comparison|
|GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.|
|Description||Spatial and temporal data processing engine for extreme data scale||Large scale data warehouse service with append-only tables||High performance Time Series DBMS|
|Primary database model||Relational DBMS||Relational DBMS||Time Series DBMS|
|Secondary database models||Time Series DBMS||Relational DBMS|
|Developer||GeoSpock||Kx Systems, a division of First Derivatives plc|
|Initial release||2010||2000 kdb was released 2000, kdb+ in 2003|
|Current release||2.0, September 2019||3.6, May 2018|
|License Commercial or Open Source||commercial||commercial||commercial free 32-bit version|
|Cloud-based only Only available as a cloud service||yes||yes||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||hosted||hosted||Linux|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||no||yes|
|Secondary indexes||temporal, categorical||no||yes table attribute 'grouped'|
|SQL Support of SQL||ANSI SQL for query only (using Presto)||yes||SQL-like query language (q)|
|APIs and other access methods||JDBC||RESTful HTTP/JSON API||HTTP API|
|Supported programming languages||.Net|
|Triggers||no||no||yes with views|
|Partitioning methods Methods for storing different data on different nodes||Automatic sharding||none||horizontal partitioning|
|Replication methods Methods for redundantly storing data on multiple nodes||Source-replica replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no||no similar paradigm used for internal processing|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||no||no||yes|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||no Since BigQuery is designed for querying data||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||no||yes|
|User concepts Access control||Access rights for users can be defined per table||Access privileges (owner, writer, reader) on dataset, table or view level Google Cloud Identity & Access Management (IAM)||rights management via user accounts|
|More information provided by the system vendor|
|Specific characteristics||Integrated columnar database & programming system for streaming, real time and historical...|
|Competitive advantages||provides seamless scalability; runs on industry standard server platforms; is top-ranked...|
|Typical application scenarios||tick database streaming sensor data massive intelligence applications oil and gas...|
|Key customers||Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...|
|Market metrics||kdb+ performance and reliability proven by our customers in critical infrastructure...|
|Licensing and pricing models||upon request|
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|3rd parties||CData: Connect to Big Data & NoSQL through standard Drivers.|
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