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  1. DZone
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  4. Clusterpoint Disrupts Cloud Database Market with Clusterpoint 4 Computing Engine

Clusterpoint Disrupts Cloud Database Market with Clusterpoint 4 Computing Engine

Clusterpoint 4 combines instantly scalable database and computational power.

Colleen Williams user avatar by
Colleen Williams
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Oct. 16, 15 · News
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Unlike other NoSQL databases available today, Clusterpoint 4 supports ACID-compliant multi-document transactions and a JavaScript-based computational model, ensuring strong consistency and providing massive parallelism.

Clusterpoint, a database vendor providing Database-As-A-Service (DBAAS), today announced the availability of Clusterpoint 4, an evolution of its database software now becoming a computing engine. This unique platform combines an instantly scalable document-oriented database and computing so businesses can process and analyze large amounts of data in real-time at a reasonable cost

Because datasets are much bigger today than what can be stored in the memory of a single server, businesses are looking beyond traditional relational databases, which no longer provide the right computational platform for today’s “big data” computing needs. Moreover, businesses today want to do more than access information in a static format; they want to analyze and transform their data to gain valuable insights about their business quickly and cost effectively.

Clusterpoint 4 solves these data challenge by unifying computational power and data. Clusterpoint has built a distributed cloud computer that can share data among multiple computational nodes and execute code on those nodes next to the data. Furthermore, because Clusterpoint 4 was designed as a complete relational database replacement for businesses today, they built a new data manipulation and querying language in JS/SQL. JavaScript, a universal non-proprietary language, now can be utilized for data retrieval and data transformation in a familiar SQL structure. This truly makes Clusterpoint a computing engine that can not only store data, but process data and run arbitrary computations.

The Clusterpoint 4 Computing Engine was built on top of Clusterpoint 3, creating a distributed document-oriented database that supports persisting data structures while building efficient numeric, full-text and geospatial indices.

To be considered a real replacement for relational databases, Clusterpoint 4 supports ACID-compliant multi-document transactions and a rich computational model based on JavaScript — two features often ignored by other NoSQL databases in the market today. For many use cases it’s imperative to work on multiple data objects within one transaction to guarantee immediate consistency. Another important aspect of the database is its computational capabilities. The Clusterpoint 4 API is based on the concept that a database needs to allow arbitrary computation to be done on the data inside of the database. This allows various stages of retrieval to use arbitrary JavaScript code to transform the data. Additionally, JavaScript code accesses indices instead of raw objects, providing greater efficiency.

“With Clusterpoint 4, we want to reduce complexity and costs of existing IT infrastructure and enable real-time processing of data on a massive scale. We want our users, like developers, to import their raw data and then leverage the power of our computing engine to transform that data into something that has business benefits, exactly when and how they want it,” said Zigmars Raascevskis, CEO of Clusterpoint.

Utilizing the Clusterpoint Cloud, users can scale instantly and get on-demand computational resources at a millisecond granularity. In addition, businesses benefit from a unique pricing model -- a true pay-per-use model that is disrupting the tiered pricing model of today’s traditional Database-As-A-Service (DBAAS) offerings — which no other DBAAS company provides.

For more detailed information about Clusterpoint 4, please visit their blog.

Relational database Computing Engine Data (computing) Cloud database Cloud Document-oriented database

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  • Cloud Database Services Compared: AWS, Microsoft, Google, and Oracle
  • Lessons Learned Moving From On-Prem to Cloud Native
  • Enterprise Computing and the Public Cloud Dilemma

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