Time Series Databases by Ted Dunning & Ellen Friedman

Author:Ted Dunning & Ellen Friedman
Language: eng
Format: epub, pdf
Tags: COMPUTERS / Databases / Data Mining
ISBN: 9781491914717
Publisher: O’Reilly Media
Published: 2014-11-19T16:00:00+00:00

Figure 3-6. Data flow for the direct blob insertion approach. The catcher stores data in the cache and writes it to the restart logs. The blob maker periodically reads from the cache and directly inserts compressed blobs into the database. The performance advantage of this design comes at the cost of requiring access by the renderer to data buffered in the cache as well as to data already stored in the time series database.

What are the advantages of this direct blobbing approach? A real-world example shows what it can do. This architecture has been used to insert in excess of 100 million data points per second into a MapR-DB table using just 4 active nodes in a 10-node MapR cluster. These nodes are fairly high-performance nodes, with 16 cores, lots of RAM, and 12 well-configured disk drives per node, but you should be able to achieve performance within a factor of 2–5 of this level using most hardware.

This level of performance sounds like a lot of data, possibly more than most of us would need to handle, but in Chapter 5 we will show why ingest rates on that level can be very useful even for relatively modest applications.

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