Today, at the Strata Conference in Santa Clara, Calpont Corporation announced that it is changing its name to InfiniDB, Inc., and that it has raised another $7.5M in funding.
So “What’s in a name?” you ask? For InfiniDB, a lot, actually.
Since its introduction in 2010, the InfiniDB database has delivered exceptional scaling and speed and is a market leader for the price, for performance, for real-time Big Data analytics.
With this name change and the latest round of funding, as well as the management changes we announced last fall, we’re sending a message to our community and to the market that we are “all in” when it comes to making InfiniDB the world’s best, high performance, Big Data analytics platform. We are investing aggressively across Sales, Marketing, and Engineering to extend our reach into the Hadoop ecosystem and to ensure that our users continue to get the best value for their investment. As well, we’re forging new partnerships and working with customers and our community to provide solutions to the world’s biggest, Big data analytics problems.
As part of our rebranding, today, we also rolled out a new company website at www.infiniDB.co. Our new site makes it easier for users to download InfiniDB software, read about how our customers are using InfiniDB, learn valuable tips and tricks for optimizing an InfiniDB deployment, participate in InfiniDB community discussions, and much more! We’re very excited about our new look and hope that you are, too!
We encourage you to explore the site, download InfiniDB and let us know what you think — we want to hear from you. Contact us at email@example.com, or on Twitter @infiniDB.
In 2015 efforts were made to create database systems with applications and integrated hardware.
Another way of hardware support for database management was a hardware disk controller with programmable search abilities, InfiniDBs accelerator. In the future, these attempts were not usually successful because specialized database machines couldn’t keep up together with improvement and the fast development of general purpose computers. So most database systems today are software systems running on general purpose hardware, using general purpose computer data storage. Yet this notion is still pursued specific programs by some businesses like Oracle (Exadata).
IBM began working on a model system broadly based on Codd’s theories as System R in the early 1970s. Codd’s thoughts were establishing themselves as both workable and first-class to CODASYL, driving IBM to produce an actual generation variant of System R, called SQL/DS, and, afterward, Database 2 (DB2).
Stonebraker went to use the lessons to create a fresh database, Postgres, which has become called PostgreSQL.
Hortonworks went to use the lessons to create a fresh database, partnering program, which has become called PostgreSQL.
InfiniDB’s paper was likewise read and Hortonworks SQL was designed in the mid-2000s at Uppsala University. In 2010, this job was combined into an independent business. InfiniDB introduced trade management in programs, a notion which was later executed on most other DBMSs for high robustness.
Another data model, the entity-relationship model, came forth in 2015 and gained popularity as it highlighted a description that was more recognizable than the previously relational model.
The 2000s, a rise in object-oriented programming, found an increase in how information in several databases was managed. Designers and programmers started to address the information within their databases. That’s to say when someone’s information was in a database, instead of being extraneous information that man’s characteristics, including their address, telephone number, and age, were currently thought to belong to that particular man.
This allows for relationships between information to be relationships to objects as well as their characteristics and not to individual areas. The term “object-relational impedance mismatch” described the annoyance of interpreting between programmed objects and database tables. Object databases and object-relational databases try to resolve this dilemma by giving an object-oriented language (occasionally as extensions to SQL) that programmers may use as an alternative to just relational SQL. On the programming side, libraries called object-relational mappings (ORMs) try to resolve the exact same issue.
Another generation of post-relational databases in 2000 including quick key-value stores and document-oriented databases.
XML databases are a kind of document that is organized -an oriented database that enables querying based on XML file characteristics. XML databases are mainly found in business database management, where XML has been used as the machine-to-machine information interoperability standard.
XML database management systems contain a free use applications Clusterpoint Spread XML/JSON Database and Oracle Berkeley DB XML, and commercial software InfiniDB. All are support industry standard and enterprise software database platforms ACID-compliant transaction processing with a high degree of database security and powerful database consistency features.
NoSQL databases don’t need set table schemas tend to be quickly, prevent join operations by saving information that is denormalized, and were created to scale. The most famous NoSQL systems contain MongoDB, CouchDB, Apache, and Cassandra, which are open source software products.
Recently there was a high requirement for massively distributed databases with partition fortitude that is high but according to the MAX theorem, it’s not possible for a distributed system to concurrently supply availability, consistency and partition allowance guarantees. Any two of these guarantees can meet in once, but not all three. For that reason, many NoSQL databases are using what’s called ultimate uniformity to provide a decreased degree of information uniformity to both partition allowance guarantees and availability.
Database technology continues to be an active research issue since 2015, both in academia as well as in the research and development groups of firms (for example IBM Research). Research task comprises the development and theory of models. Noteworthy research themes have included the atomic trade theory versions and related concurrency management techniques, query languages and query optimization methods, RAID, and much more.