My name is Yiqun Zhang and I worked as a software engineering intern on the SQL core team at Volt Active Data during the summer. The experience of working with so many smart and talented people was so much fun. I was proud to be part of the team. My work focused mainly on the […]
Bringing Rack-Aware Topology to Volt Active Data
Getting around the Transparent Huge Pages trap in Linux
A couple of weeks ago, an interesting issue came up in the field. The symptom was that the resident set size (RSS) of the Volt Active Data process would keep growing when the database was idle. The symptom only manifested itself on Red Hat Enterprise Linux (RHEL) 6.6 in KVM. There was no client workload, […]
NoSQL vs. NewSQL: Choosing the Right Tool
Trying to choose a database to solve a problem (or a whole set of them)? Here’s a quick rundown of the advantages – and disadvantages – of NoSQL versus NewSQL. Choosing the right tool for the job at hand is 80 percent of getting to a solution; the other 20 percent is really understanding the […]
FoundationDB’s Lesson: A Fast Key-Value Store is Not Enough
The sale and subsequent closure of FoundationDB cut short something of a grand experiment. FoundationDB, conceived as a Key-Value store, had decided to add flexibility in the form of programming and query-model “Layers” on top of its core KV store. First up was SQL, software that ran on top of core FoundationDB and provided SQL […]
How Docker Simplifies Distributed Systems Development at Volt Active Data
Working on distributed systems is fun, but not easy! As a software engineer at Volt Active Data, a big chunk of my time is spent testing software on a cluster of machines as part of new feature development and also for customer issue reproduction. Any software engineer who does this on a daily basis knows […]
Simplifying the (complex) Lambda Architecture
The Lambda Architecture defines a robust framework for ingesting streams of fast data while providing efficient real-time and historical analytics. In Lambda, immutable data flows in one direction: into the system. The architecture’s main goal is to execute OLAP-type processing faster – in essence, reduce columnar analytics from every couple of seconds to 100ms or […]
Optimizing Index Performance – A CMU Intern’s Work at Volt Active Data
My name is Yetian Xia. I worked as a software engineering intern at Volt Active Data during the summer, working with the core team. My favorite project was optimizing the performance of deleting entries from a low-cardinality non-unique tree index. Index is used to increase the speed of looking up a row, and is heavily […]
Best Practices for Index Optimization in Volt Active Data
Indexes provide a classic “space for speed” trade-off. They add to the persistent memory footprint of your application data but they make query filtering significantly faster. They also represent a trade-off that sacrifices write performance for read performance, on the assumption that indexed data will be filtered by queries more frequently than it is modified. […]
Volt Active Data In-Memory Database Achieves Best-In-Class Results, Running in the Cloud, On the YCSB Benchmark
The development team at Volt Active Data recently ran Volt Active Data v4.2 against the Yahoo Cloud Serving Benchmark (YCSB), an industry-standard performance benchmark for cloud databases. We ran our test on as realistic a cluster setup as possible: commodity hardware that we could easily book as spot instances on EC2, with features like durability […]