Solid-state memory
Discussion of how developments in solid-state memory will affect database management. Related subjects include:
- Data warehouse appliances
- (in The Monash Report) The future of diskless PCs
MarkLogic 5, and why you might care
MarkLogic is releasing MarkLogic 5. Key elements of the announcement are:
- More-of-the-same in line with MarkLogic’s core positioning.
- A new bi-directional Hadoop connector.
- A free MarkLogic Express edition, limited in license terms more than in actual features, as per Slide 27 of the deck MarkLogic graciously supplied for me to post.
Also, MarkLogic is early with a feature that most serious DBMS vendors will soon have – support for tiered storage, with writes going first to solid-state storage, then being flushed to disk via a caching-style algorithm.* And as befits a sometime search-engine-substitute, MarkLogic has finally licensed a large set of document filters, from an Australian company called Isys. Apparently, the special virtue of the Isys filters is that they’re good at extracting not only text, but metadata as well.
*If there’s a caching algorithm that doesn’t contain a major element of LRU (Least Recently Used), I don’t recall ever hearing about it.
MarkLogic seems to have settled on a positioning that, although distressingly buzzword-heavy, is at least partly based upon reality. The real part includes:
- MarkLogic is a serious, enterprise-class DBMS (see for example Slide 12 of the MarkLogic deck) …
- … which has been optimized from the getgo for poly-structured data.
- MarkLogic can and does scale out to handle large amounts of data.
- MarkLogic is a general-purpose DBMS, suitable for both short-request and analytic tasks.
- MarkLogic is particularly well suited for analyses with long chains of “progressive enhancement” (MarkLogic’s favorite term when talking about derived data).
- MarkLogic often plays the role of a content assembler and/or search engine, and the people who use MarkLogic in those ways are commonly doing things that can be described as research and analysis.
Based on that reality, MarkLogic talks a lot about Volume, Velocity, Variety, Big Data, unstructured data, semi-structured data, and big data analytics.
| Categories: Hadoop, Market share and customer counts, MarkLogic, Scientific research, Solid-state memory, Structured documents, Text | 1 Comment |
HP systems soundbites
It is widely rumored that there will be a leadership change at HP (Meg Whitman in, Leo Apotheker out). In connection with that, I found myself holding forth on points such as:
- HP needs to make outstanding enterprise systems again.
- They fell away from that target under Mark Hurd, but they surely can hit it again, based on the remnants of DEC (Digital Equipment Corporation), Tandem, the higher-end part of Compaq, and of course the original HP systems group.
- In particular:
- Rumors say that Oracle Exadata 1 boxes, made by HP, were much lower quality than Exadata 2 boxes made by Sun.
- HP Neoview was a waste of good engineering talent.
- I’d like to see a few excellent Vertica appliances.
- I hope the SAP HANA appliances go well, whenever HANA finally becomes a serious product.
- The general move from disk to solid-state memory should offer some opportunities.
| Categories: Exadata, HP and Neoview, SAP AG, Solid-state memory, Vertica Systems | Leave a Comment |
Are there any remaining reasons to put new OLTP applications on disk?
Once again, I’m working with an OLTP SaaS vendor client on the architecture for their next-generation system. Parameters include:
- 100s of gigabytes of data at first, growing to >1 terabyte over time.
- High peak loads.
- Public cloud portability (but they have private data centers they can use today).
- Simple database design — not a lot of tables, not a lot of columns, not a lot of joins, and everything can be distributed on the same customer_ID key.
- Stream the data to a data warehouse, that will grow to a few terabytes. (Keeping only one year of OLTP data online actually makes sense in this application, but of course everything should go into the DW.)
So I’m leaning to saying: Read more
Kaminario goes (mainly) flash
Kaminario, which used to be in the business of solid state storage via DRAM, now is emphasizing hybrid DRAM/flash storage appliances instead. The reason is evidently price. Per terabyte of primary storage (before mirroring onto disk and so on):
- A Kaminario K2 DRAM-only appliance costs $100K.
- A Kaminario K2 flash-only appliance costs $30K (but nobody buys that configuration).
- A typical Kaminario K2 hybrid DRAM/flash appliance might cost $35K (which tells us that there’s a lot more flash than DRAM).
Kaminario positions DRAM as where you focus your most write-intensive/ bottlenecking loads, such as logging or temp space, with the primary benefit being performance and a secondary benefit being slowing the wear on your flash.
| Categories: Kaminario, OLTP, Pricing, Solid-state memory | 6 Comments |
Couchbase technical update
My Couchbase business update with Bob Wiederhold was very interesting, but it didn’t answer much about the actual Couchbase product. For that, I talked with Dustin Sallings. We jumped around a lot, and some important parts of the Couchbase product haven’t had their designs locked down yet anyway. But here’s at least a partial explanation of what’s up.
memcached is a way to cache data in RAM across a cluster of servers and have it all look logically like a single memory pool, extremely popular among large internet companies. The Membase product — which is what Couchbase has been selling this year — adds persistence to memcached, an obvious improvement on requiring application developers to write both to memcached and to non-transparently-sharded MySQL. The main technical points in adding persistence seem to have been:
- A persistent backing store (duh), namely SQLite.
- A change to the hashing algorithm, to avoid losing data when the cluster configuration is changed.
Couchbase is essentially Membase improved by integrating CouchDB into it, with the main changes being:
- Changing the backing store to CouchDB (duh). This will be in the first Couchbase release.
- Adding cross data center replication on CouchDB’s consistency model. This will not, I believe, be in the first Couchbase release.
- Offering CouchDB’s programming and query interfaces as an option. So far as I can tell, this will be implemented straightforwardly in the first Couchbase release, with elegance planned for later down the road.
Let’s drill down a bit into Membase/Couchbase clustering and consistency. Read more
| Categories: Cache, Clustering, Couchbase, memcached, Memory-centric data management, MySQL, Parallelization, Solid-state memory | 8 Comments |
MongoDB users and use cases
I spoke with Eliot Horowitz and Max Schierson of 10gen last month about MongoDB users and use cases. The biggest clusters they came up with weren’t much over 100 nodes, but clusters an order of magnitude bigger were under development. The 100 node one we talked the most about had 33 replica sets, each with about 100 gigabytes of data, so that’s in the 3-4 terabyte range total. In general, the largest MongoDB databases are 20-30 TB; I’d guess those really do use the bulk of available disk space. Read more
| Categories: Data models and architecture, Games and virtual worlds, Log analysis, MongoDB, NoSQL, Solid-state memory, Specific users, Splunk, Telecommunications, Web analytics | 13 Comments |
Notes from the Fusion-io S-1 filing
Fusion-io has filed for an initial public offering. With public offerings go S-1 filings which, along with 10-Ks, are the kinds of SEC filing that typically contain a few nuggets of business information. Notes from Fusion-io’s S-1 include:
Fusion-io is growing very, very fast, doubling or better in revenue every 6 months.
Fusion-io’s marketing message revolves around “data centralization”. Fusion-io is competing against storage-area networks and storage arrays.
Fusion-io’s list of application types includes
… systems dedicated to decision support, high performance financial analysis, web search, content delivery and enterprise resource planning.
Fusion-io says it has shipped over 20 petabytes of storage.
Fusion-io has a shifting array of big customers, including OEMs: Read more
| Categories: Analytic technologies, Data warehousing, Facebook, Solid-state memory, Storage | Leave a Comment |
Oracle and Exadata: Business and technical notes
Last Friday I stopped by Oracle for my first conversation since January, 2010, in this case for a chat with Andy Mendelsohn, Mark Townsend, Tim Shetler, and George Lumpkin, covering Exadata and the Oracle DBMS. Key points included: Read more
Notes on short-request scale-out MySQL
A press person recently asked about:
… start-ups that are building technologies to enable MySQL and other SQL databases to get over some of the problems they have in scaling past a certain size. … I’d like to get a sense as to whether or not the problems are as severe and wide spread as these companies are telling me? If so, why wouldn’t a customer just move to a new database?
While that sounds as if he was asking about scale-out relational DBMS in general, MySQL or otherwise, short-request or analytic, it turned out that he was asking just about short-request scale-out MySQL. My thoughts and comments on that narrower subject include(d) but are not limited to: Read more
Teradata integrates in solid-state storage
For once, I think Teradata’s annual hardware refresh is pretty interesting, because of the integration of flash storage into its high-end “active enterprise data warehouse” product line. The essence of the announcement is:
- Teradata is rolling out a new appliance,* the 6680, which combines hard-disk and solid-state drives, relying on Teradata Virtual Storage.
- Teradata is also rolling out a hard-disk-based appliance,* the 6650, in a more routine annual refresh.
| Categories: Data warehouse appliances, Pricing, Solid-state memory, Teradata | 3 Comments |