Using a technology called structured encryption, MongoDB users can perform equality search queries on encrypted data directly, without first decrypting it, and can do so even on data in which the encryption scheme was randomized. Until today, the acquisition was kept quiet - until today so that MongoDB could show how important this initiative is. As it turns out, MongoDB acquired a company over a year ago called Aroki Systems, which was focused on cryptography, specifically for this purpose. Meanwhile, MongoDB is seeking to make it easier and more attractive to encrypt data, helping customers stay in compliance with data protection regulations while still maintaining queryable functionality. These are important changes for performance, especially in a database that at one time was optimized almost exclusively for write performance and had little support for secondary indexes.
#Mongodb compass export series#
In addition to those previously released capabilities, MongoDB also announced a special secondary and geo-indexing, as well as read performance improvements, specifically for time series collections. That’s why, after the release of MongoDB 5.0, time-series collections in that version were enhanced with several features like, support for sharded clusters, data tiering, multi-deletes, cardinality handling improvements, handling of missing data points (with densification and gap-filling), and compression to reduce storage overhead. Time-series applications are often deployed to specific databases specialized for those workloads ( InfluxDB being a canonical example), but MongoDB feels that is inefficient and unnecessary. These are not the areas that I necessarily see as the most exciting, but since the company sees these as the big haul, let’s start with time-series data workloads on one hand and something new called “queryable encryption” on the other. The execs at MongoDB see two areas of innovation to be their banner announcements. Register Here Headlining MongoDB’s announcement Join us at the leading event on applied AI for enterprise business and technology decision makers in-person July 19 and virtually from July 20-28.
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