We’re Proud to Partner with These Companies
Datavail Corporation is the largest provider of remote database administration (DBA) services in North America, offering 24×7 managed database services, development DBA services, and business intelligence solutions. The company specializes in Oracle, Oracle E-Business Suite, Microsoft SQL Server, MySQL, MongoDB, DB2 and SharePoint, and provides flexible onsite/offsite, onshore/offshore service delivery options to meet each customer’s unique business needs. Datavail’s Development, Tuning & Automation practice helps enterprises build a DevOps team that is inclusive across all tiers and supports a proactive approach. Founded in 2007, Datavail is based in Broomfield, Colorado and supports enterprise clients located worldwide. For more information, visit www.datavail.com.
With more than 3,000 customers worldwide, Percona is the only company that delivers enterprise-class solutions for both MySQL® and MongoDB® across traditional and cloud-based platforms. The company provides Software, Support, Consulting, and Managed Services to some of the largest and most well-known brands on the Internet such as Cisco Systems, Time Warner Cable, Alcatel-Lucent, Groupon, and the BBC, as well as to many smaller companies looking to maximize application performance while streamlining database efficiencies. Well established as thought leaders, Percona experts author content for the Percona Database Performance Blog. The popular Percona Live conferences draw attendees and acclaimed speakers from around the world. For more information, visit www.percona.com.
Recent News & Blogs
Boulder, Colo., February 23, 2017 – SlamData Inc., the leading open source analytics company for modern unstructured data today announced that it has raised a $6.7M Series A funding round, led by Shasta Ventures. The investment will drive further development of the firm’s breakthrough analytics solution: a single application for natively exploring, visualizing and embedding analytics against unstructured data sources including NoSQL, Hadoop, and cloud API’s.read more
SlamData just released its first update of 2017, SlamData 4.1.1. It delivers a number of new UI enhancements, performance improvements, new charts, as well as commercial releases for the Couchbase, MarkLogic and Spark/Hadoop connectors.read more
Welcome to the SlamData getting started video. Let’s jump right in. By default, SlamData runs on port 20223. You can change the port it runs on by modifying the quasar-config.json file. By default, this file is located in the following directories on Windows, Mac and Linux.read more
Who Is Using SlamData?
Whitepaper: The Characteristics of NoSQL Analytics Systems
by John De Goes, CTO and Co-Founder of SlamData
Semistructured data, called NoSQL data in this paper, is growing at an unprecedented rate. This growth is fueled, in part, by the proliferation of web and mobile applications, APIs, event-oriented data, sensor data, machine learning, and the Internet of Things, all of which are disproportionately powered by NoSQL technologies and data models.
This paper carves out a single concern, by focusing on the system-level capabilities required to derive maximum analytic value from a generalized model of NoSQL data. This approach leads to eight well-defined, objective characteristics, which collectively form a precise capabilities-based definition of a NoSQL analytics system.
These capabilities are inextricably motivated by use cases, but other considerations are explicitly ignored. They are ignored not because they are unimportant (quite the contrary), but because they are orthogonal to the raw capabilities a system must possess to be capable of deriving analytic value from NoSQL data.
Table of Contents
- The Nature of NoSQL Data
- NoSQL Databases
- Big Data
- A Generic Data Model for NoSQL
- Approaches to NoSQL Analytics
- Coding & ETL
- Real-Time Analytics
- Relational Model Virtualization
- First-Class NoSQL Analytics
- Characteristics of NoSQL Analytics Systems
- Generic Data Model
- Isomorphic Data Model
- Unified Schema/Data
- Polymorphic Queries
- Dynamic Type Discovery & Conversion
- Structural Patterns