DBMS > Drizzle vs. HEAVY.AI
System Properties Comparison Drizzle vs. HEAVY.AI
Please select another system to include it in the comparison.
|Editorial information provided by DB-Engines
|Drizzle Xexclude from comparison
|HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 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.
|MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.
|A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
|Primary database model
|Secondary database models
|Drizzle project, originally started by Brian Aker
|7.2.4, September 2012
|5.10, January 2022
|License Commercial or Open Source
|Open Source GNU GPL
|Open Source Apache Version 2; enterprise edition available
|Cloud-based only Only available as a cloud service
|DBaaS offerings (sponsored links) Database as a Service
Providers of DBaaS offerings, please contact us to be listed.
|C++ and CUDA
|Server operating systems
|Typing predefined data types such as float or date
|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.
|SQL Support of SQL
|yes with proprietary extensions
|APIs and other access methods
|Supported programming languages
|All languages supporting JDBC/ODBC/Thrift
|Server-side scripts Stored procedures
|no hooks for callbacks inside the server can be used.
|Partitioning methods Methods for storing different data on different nodes
|Sharding Round robin
|Replication methods Methods for redundantly storing data on multiple nodes
|MapReduce Offers an API for user-defined Map/Reduce methods
|Consistency concepts Methods to ensure consistency in a distributed system
|Foreign keys Referential integrity
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|Concurrency Support for concurrent manipulation of data
|Durability Support for making data persistent
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|Pluggable authentication mechanisms e.g. LDAP, HTTP
|fine grained access rights according to SQL-standard
More information provided by the system vendor
We invite representatives of system vendors to contact us for updating and extending the system information,
Related products and services
We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
|HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
|DB-Engines blog posts
MySQL won the April ranking; did its forks follow?
|Recent citations in the news
HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
Big Data Analytics: A Game Changer for Infrastructure
Making the most of geospatial intelligence
The insideBIGDATA IMPACT 50 List for Q4 2023
ChatGPT Confirms Data Breach, Raising Security Concerns
provided by Google News
Share this page