Category: Streaming/Kafka
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5 min read
When NoSQL Isn’t Enough: The Need for a Stronger Data Platform
Read more: When NoSQL Isn’t Enough: The Need for a Stronger Data PlatformIntroduction NoSQL databases and data platforms have gained widespread adoption over the past decade, offering flexible schema design, horizontal scalability, and fast data ingestion. While NoSQL databases are an unquestioned market success, they are not a silver bullet. Businesses handling mission-critical, high-velocity…
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5 min read
Understanding Volt Active Stream Processing
Read more: Understanding Volt Active Stream ProcessingProcessing data streams in real time has become essential for modern businesses. The rapid increase in data generation and the demand for immediate decision-making have rendered traditional batch processing inadequate. Simply collecting and analyzing data after the fact is no longer enough—companies…
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5 min read
Top 3 Kafka Streams Challenges
Read more: Top 3 Kafka Streams ChallengesWe’ve been writing a lot about challenges lately. We recently wrote about API challenges – now we’re discussing challenges with Kafka Streams. Volt is very big on Kafka, as we specialize in complementing it in a really powerful way to allow enterprises to get the most…
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5 min read
Top 5 Real-Time Data Processing Trends of 2023
Read more: Top 5 Real-Time Data Processing Trends of 20232023 was a huge year for real-time data processing. Enterprises are more focused than ever using real-time data to guide the path forward, and things like AI are changing the game. As technology continues to evolve, real-time data processing has transformed from something closer…
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5 min read
New Benchmark: Volt Very Cost-Effective at Scale on Amazon Hardware
Read more: New Benchmark: Volt Very Cost-Effective at Scale on Amazon HardwareVolt has been involved with the Yahoo! Cloud Serving Benchmark (YCSB) for some time. Every now and then we re-run the benchmark to see how we’re holding up. We recently re-ran it against newer Amazon hardware and discovered that: We’ve also made it possible…
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5 min read
How to Add Real-Time Decisioning to Streaming Data
Read more: How to Add Real-Time Decisioning to Streaming DataStreaming data has become practically ubiquitous. From social media feeds to IoT sensors, businesses are now inundated with real-time data. The challenge is not only to store this data but also to make sense of it and act on it quickly. This…
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5 min read
When Does Streaming Data Become Real-Time Data?
Read more: When Does Streaming Data Become Real-Time Data?We’ve been hearing a lot about real-time data platforms and also about streaming data and streaming data-enabling messaging technology such as Apache Kafka. The idea is to turn your streaming data into real-time data by using it while it still has value.…
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5 min read
Why Streaming Data Platforms Need True Real-Time Decisioning
Read more: Why Streaming Data Platforms Need True Real-Time DecisioningSimply put: in the year 2023 and for the foreseeable future, businesses need to be able to process and analyze data in real time to remain competitive. Streaming data platforms such as Google Cloud Platform, Microsoft Azure, Databricks, Snowflake, AWS Kinesis, and…
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5 min read
Top 5 Apache Kafka Use Cases: When to Use Kafka
Read more: Top 5 Apache Kafka Use Cases: When to Use KafkaApache Kafka is now the official gatekeeper of streaming data. It’s a distributed data store designed and perfectly calibrated to ingest and process streaming data (ie, data continuously generated by thousands of sources) in real time. As both the amount and value of…
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5 min read
Kafka Event Stream Processing at Scale: Common Kafka Challenges
Read more: Kafka Event Stream Processing at Scale: Common Kafka ChallengesEveryone has Kafka issues. Well, maybe not everyone, but most companies that end up using Apache Kafka in any meaningful way do end up facing certain Kafka challenges, most of which aren’t necessarily easy to resolve. First off — why are companies…
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5 min read
What is Streaming Data?
Read more: What is Streaming Data?Streaming data is data that flows in continuously from highly distributed sources. These data streams are constantly feeding data that data platforms can use or act upon dynamically and in real time, without the need to download or batch it first. Data streams…
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