InfoQ Homepage NoSQL Content on InfoQ
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Why a Serverless Data API Might be Your Next Database
In this article, author Pieter Humphrey discussed database as a service (DBaaS) and serverless data API for cloud based data management.
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Beyond the Database, and beyond the Stream Processor: What's the Next Step for Data Management?
Databases have been around forever with the same shape: you make a request to your data and then you receive an answer. Now, stream processors came along with a different approach: data isn’t locked up, it is in motion. Understand how stream processors and databases relate and why there is an emerging new category of databases that focus on data that stays in place as well as data that moves.
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Interview with RavenDB Founder Oren Eini
RavenDB is a NoSQL document database with multi-document ACID transactions and smart document compression. To learn more about the recent RavenDB 5 release and RavenDB in general, we’ve invited Oren Eini, creator of RavenDB and CEO of Hibernating Rhinos, to join us.
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Applied Probability - Counting Large Set of Unstructured Events with Theta Sketches
In this article, author Ronen Cohen discusses the solution to processing the event data using Theta Sketches and technologies like HBase and Kafka.
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Book Review: Developer, Advocate!
Developer, Advocate! is a set of interviews with prominent technologists, covering what drives their interest and enthusiasm in the industry. The brevity of each interview provides direct information and insight that can be read separately at any time, in any order, enabling those with busy schedules to read, put down, and repeat.
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How to Use Redis TimeSeries with Grafana for Real-Time Analytics
In this article, author Roshan Kumar discusses how a purpose-built database like RedisTimeSeries can be used to manage time-series data. He also shows how to visualize this data in a Grafana dashboard.
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Postgres Handles More Than You Think
Thinking about scaling beyond Postgres with a data store like Redis or Elasticsearch? Think again before adopting a complex infrastructure. Postgres can scale for heavy loads and offers powerful features which are not obvious at first sight. For example, it's possible to enable in-memory caching, text search, specialized indexing, and key-value storage. Article
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Understanding Serverless: Tips and Resources for Building Servicefull Applications
There are still many misconceptions and concerns regarding serverless solutions. Vendor lock-in, tooling, cost management, cold starts, monitoring and the development lifecycle are all hot topics where serverless technologies are concerned. This article shares tips and resources to guide serverless newcomers towards building powerful, flexible and cost-effective serverless applications.
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How to Use Open Source Prometheus to Monitor Applications at Scale
In this article, the author discusses how to collect metrics and achieve anomaly detection from streaming data using Prometheus, Apache Kafka and Apache Cassandra technologies.
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Real-Time Data Processing Using Redis Streams and Apache Spark Structured Streaming
Structured Streaming, introduced with Apache Spark 2.0, delivers a SQL-like interface for streaming data. Redis Streams enables Redis to consume, hold and distribute streaming data between multiple producers and consumers. In this article, author Roshan Kumar walks us through how to process streaming data in real time using Redis and Apache Spark Streaming technologies.
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Back to the Future with Relational NoSQL
This article outlines some of the consistency issues NoSQL databases have with distributed transactions, showing how FaunaDB has solved the problems using the Calvin protocol and a virtual clock.
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Spark Application Performance Monitoring Using Uber JVM Profiler, InfluxDB and Grafana
In this article, author Amit Baghel discusses how to monitor the performance of Apache Spark based applications using technologies like Uber JVM Profiler, InfluxDB database and Grafana data visualization tool.
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Live Webinar presented by Cockroach Labs |
Q&A moderated by InfoQ
This webinar dives deep into the internals of CockroachDB, exploring how the database uses KV at the storage layer to effectively distribute data, how Raft and MVCC are used to guarantee serializable isolation for transactions, how to tie data to a location to help with performance, and more.