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更新于 : Mar 29, 2017
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这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
Mar 2017
暂缓 ? 谨慎行事

We continue to see organizations chasing "cool" technologies, taking on unnecessary complexity and risk when a simpler choice would be better. One particular theme is using distributed, Big Data systems for relatively small data sets. This behavior prompts us to put Big Data envy on hold once more, with some additional data points from our recent experience. The Apache Cassandra database promises massive scalability on commodity hardware, but we have seen teams overwhelmed by its architectural and operational complexity. Unless you have data volumes that require a 100+ node cluster, we recommend against using Cassandra. The operational team you'll need to keep the thing running just isn't worth it. While creating this edition of the Radar, we discussed several new database technologies, many offering "10x" performance improvements over existing systems. We're always skeptical until new technology—especially something as critical as a database—has been properly proven. Jepsen provides analysis of database performance under difficult conditions and has found numerous bugs in various NoSQL databases. We recommend maintaining a healthy dose of skepticism and keeping an eye on sites such as Jepsen when you evaluate database tech.

Nov 2016
暂缓 ? 谨慎行事

We continue to see organizations chasing "cool" technologies, taking on unnecessary complexity and risk when a simpler choice would be better. One particular theme is using distributed, Big Data systems for relatively small data sets. This behavior prompts us to put Big Data envy on hold once more, with some additional data points from our recent experience. The Apache Cassandra database promises massive scalability on commodity hardware, but we have seen teams overwhelmed by its architectural and operational complexity. Unless you have data volumes that require a 100+ node cluster, we recommend against using Cassandra. The operational team you’ll need to keep the thing running just isn’t worth it. While creating this edition of the Radar, we discussed several new database technologies, many offering "10x" performance improvements over existing systems. We’re always skeptical until new technology—especially something as critical as a database—has been properly proven. Jepsen provides analysis of database performance under difficult conditions and has found numerous bugs in various NoSQL databases. We recommend maintaining a healthy dose of skepticism and keeping an eye on sites such as Jepsen when you evaluate database tech.

Apr 2016
暂缓 ? 谨慎行事

While we've long understood the value of Big Data to better understand how people interact with us, we've noticed an alarming trend of Big Data envy : organizations using complex tools to handle "not-really-that-big” Data. Distributed map-reduce algorithms are a handy technique for large data sets, but many data sets we see could easily fit in a single-node relational or graph database. Even if you do have more data than that, usually the best thing to do is to first pick out the data you need, which can often then be processed on such a single node. So we urge that before you spin up your clusters, take a realistic assessment of what you need to process, and if it fits—maybe in RAM—use the simple option.

发布于 : Apr 05, 2016
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