The future of the future: Spark, big data insights, streaming and deep learning in the cloud
Apache Spark is hailed as being Hadoop's successor, claiming its throne as the hottest Big Data platform. What the founding fathers of Spark are saying and doing about its future and its positioning in the market has never been more timely.
Read More →A rock and a hard place: Between ScyllaDB and Cassandra
How many NoSQL databases does the world really need, and how easily would you switch your existing solution for a new one? Asking these questions before setting out to build a NoSQL database is a good thing. The people behind ScyllaDB did, and now Cassandra may be between a rock and hard place.
Read More →Sparkier, faster, more: Graph databases, and Neo4j, are moving on
New players, new features, platforms, and ticking boxes. Let's talk graph with Neo4j.
Read More →Alice, the making of: Behind the scenes with the new AI assistant from Yandex
Did you ever wonder what it's like to build an AI personal assistant, or to bridge the language gap? Hint: There's big data and machine learning involved.
Read More →Towards a unifying data theory and practice: Combining operations, analytics, and streaming
We've heard the one data platform to rule them all story before. Could it be this time it's actually true? New Pivotal-backed and Spark-compatible open source solution SnappyData promises so, and we take the opportunity to look inside and around for whys, hows, and options.
Read More →TigerGraph, a graph database born to roar
Imagine your database of choice blown out of the water by a startup emerging from stealth. TigerGraph may have done just that for graph databases.
Read More →Insight platforms as a service: What they are and why they matter
The convergence of cloud, automation and collaboration has created a new class of offerings for data driven insights. We take a look at their defining characteristics, featuring analysis from Forrester and commentary from Qubole.
Read More →Raiders of the storm: The data science behind weather prediction
What kind of data and techniques are used to model and predict weather and climate? How do you reduce uncertainty and communicate complexity? Are Harvey and Irma signs of climate change, and is it going to get worse?
Read More →In-memory architecture + streaming data = Digital Twins?
The Digital Twin is a buzzword in its prime time infancy. We take a look at what it is and how it relates to modern data architectures, examining ScaleOut's adoption and implementation and comparing with other alternatives.
Read More →Kafka gets SQL with KSQL
Apache Kafka is a key component in data pipeline architectures when it comes to ingesting data. Confluent, the commercial entity behind Kafka, wants to leverage this position to become a platform for the enterprise and today is announcing a milestone on the road to ubiquity: SQL.
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