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MongoDB rival RethinkDB gets $8m in filthy valley lucre infusion

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Upstart RethinkDB has slurped $8m as venture capitalists bet that its tech can put major NoSQL document store MongoDB out to pasture.

The Series A funding round was announced on Monday and will bankroll the long-term support release of the database, along with giving the company time to develop commercial support offerings and further developer outreach.

RethinkDB is an open-source document store that is horizontally scalable and, unlike NoSQL leader MongoDB, has support for JOINS.

Like many NoSQL systems, RethinkDB is built to manipulate JSON data types with less of the administrative overhead of a traditional relational database. This comes with tradeoffs, such as eventual rather than strong consistency, and limited support for ACID* transactions.

"In some cases RethinkDB trades off write availability in favor of data consistency, so if you absolutely need high write availability and do not mind dealing with conflicts, you may be better off with a Dynamo-style system like Riak," the company cautioned.

The software is written in C++ and runs on 32- and 64-bit Linux systems, as well as Mac OS X 10.7 and above. It has drivers for Ruby, Python, and JavaScript. Though it does not have a SQL interface, the company claims its query method is "powerful, expressive and easy to learn", and is capable of doing "almost anything SQL can do" along with additional features as well.

The software is available under a GNU AGPL v3.0 license and the client drivers are covered by the Apache License v2.0.

The $8m funding round is small compared with the VC injections into companies like Basho (Riak), MongoDB Inc (MongoDB), and Datastax. Its closest contemporary, lucre wise, is ACID-compliant NoSQL firm FoundationDB, which recently closed a $17m Series A. ®

* The ACID principles: atomicity – a transaction is all or nothing; consistency – only valid data is written to the database; isolation – pretend all transactions are happening serially and the data is correct; durability – once a transaction enters the database, it is permanently preserved through the use of logs.

3 Big data security analytics techniques

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