dbShards and CodeFutures
Analysis of Code Futures and its flagship product dbShards. Related subjects include:
NewSQL thoughts
I plan to write about several NewSQL vendors soon, but first here’s an overview post. Like “NoSQL”, the term “NewSQL” has an identifiable, recent coiner — Matt Aslett in 2011 — yet a somewhat fluid meaning. Wikipedia suggests that NewSQL comprises three things:
- OLTP- (OnLine Transaction Processing)/short-request-oriented SQL DBMS that are newer than MySQL.
- Innovative MySQL engines.
- Transparent sharding systems that can be used with, for example, MySQL.
I think that’s a pretty good working definition, and will likely remain one unless or until:
- SQL-oriented and NoSQL-oriented systems blur indistinguishably.
- MySQL (or PostgreSQL) laps the field with innovative features.
To date, NewSQL adoption has been limited.
- NewSQL vendors I’ve written about in the past include Akiban, Tokutek, CodeFutures (dbShards), Clustrix, Schooner (Membrain), VoltDB, ScaleBase, and ScaleDB, with GenieDB and NuoDB coming soon.
- But I’m dubious whether, even taken together, all those vendors have as many customers or production references as any of 10gen, Couchbase, DataStax, or Cloudant.*
That said, the problem may lie more on the supply side than in demand. Developing a competitive SQL DBMS turns out to be harder than developing something in the NoSQL state of the art.
Our clients, and where they are located
From time to time, I disclose our vendor client lists. Another iteration is below, the first since a little over a year ago. To be clear:
- This is a list of Monash Advantage members.
- All our vendor clients are Monash Advantage members, unless …
- … we work with them primarily in their capacity as technology users. (A large fraction of our user clients happen to be SaaS vendors.)
- We do not usually disclose our user clients.
- We do not usually disclose our venture capital clients, nor those who invest in publicly-traded securities.
- Excluded from this round of disclosure is one vendor I have never written about.
- Included in this round of disclosure is one client paying for services partly in stock. All our other clients are cash-only.
For reasons explained below, I’ll group the clients geographically. Obviously, companies often have multiple locations, but this is approximately how it works from the standpoint of their interactions with me. Read more
CodeFutures/dbShards update
I’ve been talking a fair bit with Cory Isaacson, CEO of my client CodeFutures, which makes dbShards. Business notes include:
- 7 production users, plus an 8th imminent.
- 12-14 signed contracts beyond that.
- ~160 servers in production.
- One customer who has almost 15 terabytes of data (in the cloud).
- Still <10 people, pretty much all engineers.
- Profitable, but looking to raise a bit of growth capital.
Apparently, the figure of 6 dbShards customers in July, 2010 is more comparable to today’s 20ish contracts than to today’s 7-8 production users. About 4 of the original 6 are in production now.
NDA stuff aside, the main technical subject we talked about is something Cory calls “relational sharding”. The point is that dbShards’ transparent sharding can be done in such a way as to make many joins be single-server. Specifically:
- When a table is sufficiently small to be replicated in full at every nodes, you can join on it without moving data across the network.
- When two tables are sharded on the same key, you can join on that key without moving data across the network.
dbShards can’t do cross-shard joins, but it can do distributed transactions comprising multiple updates. Cory argues persuasively that in almost all cases this is enough; but I see cross-shard joins as a feature that should someday be added to dbShards even so.
The real issue with dbShards’ transparent sharding is ensuring it’s really transparent. Cory regards as typical a customer with a couple thousand tables, who had to change a dozen or so SQL statements to implement dbShards. But there are near-term plans to automate the number of SQL changes needed down to 0. The essence of that change is this: Read more
| Categories: Clustering, Data integration and middleware, Data models and architecture, dbShards and CodeFutures, Market share and customer counts, Transparent sharding | 1 Comment |
Transparent relational OLTP scale-out
There’s a perception that, if you want (relatively) worry-free database scale-out, you need a non-relational/NoSQL strategy. That perception is false. In the analytic case it’s completely ridiculous, as has been demonstrated by Teradata, Vertica, Netezza, and various other MPP (Massively Parallel Processing) analytic DBMS vendors. And now it’s false for short-request/OLTP (OnLine Transaction Processing) use cases as well.
My favorite relational OLTP scale-out choice these days is the SchoonerSQL/dbShards partnership. Schooner Information Technology (SchoonerSQL) and Code Futures (dbShards) are young, small companies, but I’m not too concerned about that, because the APIs they want you to write to are just MySQL’s. The main scenarios in which I can see them failing are ones in which they are competitively leapfrogged, either by other small competitors – e.g. ScaleBase, Akiban, TokuDB, or ScaleDB — or by Oracle/MySQL itself. While that could suck for my clients Schooner and Code Futures, it would still provide users relying on MySQL scale-out with one or more good product alternatives.
Relying on non-MySQL NewSQL startups, by way of contrast, would leave me somewhat more concerned. (However, if their code is open sourced. you have at least some vendor-failure protection.) And big-vendor scale-out offerings, such as Oracle RAC or DB2 pureScale, may be more complex to deploy and administer than the MySQL and NewSQL alternatives.
| Categories: Clustering, dbShards and CodeFutures, IBM and DB2, MySQL, NewSQL, NoSQL, OLTP, Open source, Oracle, Parallelization, Schooner Information Technology, Transparent sharding | 2 Comments |
Schooner pivots further
Schooner Information Technology started out as a complete-system MySQL appliance vendor. Then Schooner went software-only, but continued to brag about great performance in configurations with solid-state drives. Now Schooner has pivoted further, and is emphasizing high availability, clustered performance, and other hardware-agnostic OLTP (OnLine Transaction Processing) features. Fortunately, Schooner has some interesting stuff in those areas to talk about.
The short form of the SchoonerSQL (as Schooner’s product is now called) story goes roughly like this:
- SchoonerSQL replicates data — synchronously if the replication target is local, asynchronously if it is remote.
- Local synchronous replication provides high availability; remote asynchronous replication provides disaster recovery.
- SchoonerSQL’s local synchronous replication also provides read scale-out.
- Schooner has a partnership with Code Futures/dbShards to provide write scale-out via transparent sharding.
- SchoonerSQL has some secret sauce in replication performance. This has the effect of significantly increasing write performance (assuming you were going to replicate anyway), because otherwise you might have to slow down the master server’s write performance so that the slaves can keep up with it.
- Schooner believes it still has some single-server performance advantages as well.
| Categories: Clustering, dbShards and CodeFutures, MySQL, OLTP, Oracle, Parallelization, Schooner Information Technology | 3 Comments |
Defining NoSQL
A reporter tweeted: “Is there a simple plain English definition for NoSQL?” After reminding him of my cynical yet accurate Third Law of Commercial Semantics, I gave it a serious try, and came up with the following. More precisely, I tweeted the bolded parts of what’s below; the rest is commentary added for this post.
NoSQL is most easily defined by what it excludes: SQL, joins, strong analytic alternatives to those, and some forms of database integrity. If you leave all four out, and you have a strong scale-out story, you’re in the NoSQL mainstream. Read more
| Categories: Cassandra, dbShards and CodeFutures, MarkLogic, MySQL, Object, Open source, Petabyte-scale data management, Schooner Information Technology | 7 Comments |
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
Soundbites: the Facebook/MySQL/NoSQL/VoltDB/Stonebraker flap, continued
As a follow-up to the latest Stonebraker kerfuffle, Derrick Harris asked me a bunch of smart followup questions. My responses and afterthoughts include:
- Facebook et al. are in effect Software as a Service (SaaS) vendors, not enterprise technology users. In particular:
- They have the technical chops to rewrite their code as needed.
- Unlike packaged software vendors, they’re not answerable to anybody for keeping legacy code alive after a rewrite. That makes migration a lot easier.
- If they want to write different parts of their system on different technical underpinnings, nobody can stop them. For example …
- … Facebook innovated Cassandra, and is now heavily committed to HBase.
- It makes little sense to talk of Facebook’s use of “MySQL.” Better to talk of Facebook’s use of “MySQL + memcached + non-transparent sharding.” That said:
- It’s hard to see why somebody today would use MySQL + memcached + non-transparent sharding for a new project. At least one of Couchbase or transparently-sharded MySQL is very likely a superior alternative. Other alternatives might be better yet.
- As noted above in the example of Facebook, the many major web businesses that are using MySQL + memcached + non-transparent sharding for existing projects can be presumed able to migrate away from that stack as the need arises.
Continuing with that discussion of DBMS alternatives:
- If you just want to write to the memcached API anyway, why not go with Couchbase?
- If you want to go relational, why not go with MySQL? There are many alternatives for scaling or accelerating MySQL — dbShards, Schooner, Akiban, Tokutek, ScaleBase, ScaleDB, Clustrix, and Xeround come to mind quickly, so there’s a great chance that one or more will fit your use case. (And if you don’t get the choice of MySQL flavor right the first time, porting to another one shouldn’t be all THAT awful.)
- If you really, really want to go in-memory, and don’t mind writing Java stored procedures, and don’t need to do the kinds of joins it isn’t good at, but do need to do the kinds of joins it is, VoltDB could indeed be a good alternative.
And while we’re at it — going schema-free often makes a whole lot of sense. I need to write much more about the point, but for now let’s just say that I look favorably on the Big Four schema-free/NoSQL options of MongoDB, Couchbase, HBase, and Cassandra.
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
Updating our vendor client disclosures
Edit: This disclosure has been superseded by a March, 2012 version.
From time to time, I disclose our vendor client lists. Another iteration is below. To be clear:
- This is a list of Monash Advantage members.
- All our vendor clients are Monash Advantage members, unless …
- … we work with them primarily in their capacity as technology users. (A large fraction of our user clients happen to be SaaS vendors.)
- We do not usually disclose our user clients.
- We do not usually disclose our venture capital clients, nor those who invest in publicly-traded securities.
- Included in the list below are two expired Monash Advantage members who haven’t said they will renew, as mentioned in my recent post on analyst bias. (You can probably imagine a couple of reasons for that obfuscation.)
With that said, our vendor client disclosures at this time are:
- Aster Data
- Cloudera
- CodeFutures/dbShards
- Couchbase
- EMC/Greenplum
- Endeca
- IBM/Netezza
- Infobright
- Intel
- MarkLogic
- ParAccel
- QlikTech
- salesforce.com/database.com
- SAND Technology
- SAP/Sybase
- Schooner Information Technology
- Skytide
- Splunk
- Teradata
- Vertica