DataStax: All content tagged as DataStax in NoSQL databases and polyglot persistence
Friday, 24 May 2013
NoSQL and Full Text Indexing: Two Trends
On one side:
- DataStax with Solr
- MapR with LucidWorks Search (nb: Solr)
and on the other side:
- Riak Searching: Solr-like but custom prioprietary implementation
- MongoDB text search: custom prioprietary implementation
I’m not going to argue about the pros and cons of each of these approaches, but I’m sure you already know which of these approaches I’m in favor of.
Original title and link: NoSQL and Full Text Indexing: Two Trends (©myNoSQL)
Monday, 20 May 2013
Hadoop, Security, and DataStax Enterprise
But the eWeek article demonstrates that the same concerns [nb: about security] exist where Hadoop implementations are concerned. The article says: “It [Hadoop] was not written to support hardened security, compliance, encryption, policy enablement and risk management.”
The story goes like this: in the early days of NoSQL, when no NoSQL database had any sort of security features, people behind the projects answered: “it’s too early. we’re focusing on more important features. and you can still get around security by placing your database behind firewalls”. Today, when more and more NoSQL databases are adding security features, the story these same people are telling is quite different: “ohhh, security is critical. we don’t really see how you could run a database without these features”.
Security is always critical. And exactly the same can be said about maintaining a solid, coherent story of what you are telling your users.
Original title and link: Hadoop, Security, and DataStax Enterprise (©myNoSQL)
via: http://www.datastax.com/2013/04/hadoop-security-and-the-enterprise
Monday, 25 March 2013
Oracle and DataStax on TechCrunch
I have some serious doubts about Alex Williams’s post on TechCrunch about the connection between the recently announced results from Oracle and DataStax. To exemplify, these paragraphs don’t make a lot of sense to me:
The reason for the drop has more to do with the enterprise acceptance of online applications more than anything else, said Datatastax CEO Billy Bosworth in an interview last week.
Does it mean that enterprises are discovering online applications now?
When companies come to Datastax, they say the number one thing they need is security, Bosworth said. They are building from day one to avoid disaster scenarios.
DataStax introduced security features just recently, so I’ll assume Billy Bosworth was actually referring to fault tolerance and resilience. What ended up in the article is a different story.
Datastax has its own challenges. It competes with Amazon Web Services and all the other NoSQL providers such as 10gen.
Once again I’ll assume the author wanted to refer to Amazon Dynamo (and RDS?), but thought it’ll read better as “Amazon Web Services”.
Actually, now that I read it twice, I realize that I shouldn’t link to it. But at least I can suggest you to waste no time with it.
Original title and link: Oracle and DataStax on TechCrunch (©myNoSQL)
via: http://techcrunch.com/2013/03/24/oracle-is-bleeding-at-the-hands-of-database-rivals/
Tuesday, 5 March 2013
A Quick Tour of Internal Authentication and Authorization Security in DataStax Enterprise and Apache Cassandra
Robin Schumacher describes the new security features added to Apache Cassandra and DataStax Enterprise:
This article will concentrate on the new internal authentication and authorization (or permission management) features that are part of both open source Cassandra as well as DataStax Enterprise. Authentication deals with validating incoming user connections to a database cluster, whereas authorization concerns itself with what a logged in user can do inside a database.
I’m happy to see NoSQL databases entering the space of security as this would ease their way inside enterprises. But I fear a bit the moment when the marketing message will change from “it’s too early to provide security features” to “the first enterprise grade NoSQL database”.
Original title and link: A Quick Tour of Internal Authentication and Authorization Security in DataStax Enterprise and Apache Cassandra (©myNoSQL)
Wednesday, 13 February 2013
NoSQL on MySQL: Stating the Obvious
Matthew Aslett about Couchbase’s and DataStax’s reactions to Oracle’s announcement of MySQL support of NoSQL API:
Sure, Couchbase and DataStax laid it on a bit thick, but these are corporate blog posts – it goes with the territory.
I’ve already linked and commented about these: Couchbase’s reaction and DataStax’s reaction. What I didn’t know—more accurately I should probably write “I hoped”—is that this sort of reactions come with the “corporate” badge. But I’ll keep my hope considering the exhaustive list of reactions from other NoSQL companies.
Original title and link: NoSQL on MySQL: Stating the Obvious (©myNoSQL)
DataStax's Reaction to MySQL 5.6: Oracle’s MySQL Misses the NoSQL Mark
Jonathan Ellis in a post about MySQL 5.6 and how Oracle got the whole NoSQL wrong, considering NoSQL is, in this exact order, about scaling, continuous availability, flexibility, performance, and queryability:
The big news for MySQL 5.6 was the inclusion of “NoSQL” features in the form of a memcached api for get and put operations.
In cases like this, it’s tough to tell whether Oracle got this so wrong deliberately to sow confusion in the market, or because they really think that’s what NoSQL is about.
I know Jonathan Ellis has always had very strong opinions about the technical superiority of Cassandra and Cassandra is indeed a very solid solution, but I’m always reluctant to calling a competitor stupid and using the myopic argument “if I’m good at X and suck at Y, then what everyone is looking for is only X”.
Original title and link: DataStax’s Reaction to MySQL 5.6: Oracle’s MySQL Misses the NoSQL Mark (©myNoSQL)
via: http://www.datastax.com/dev/blog/oracles-mysql-misses-the-nosql-mark
Monday, 1 October 2012
$25 Million in C Round for DataStax
I’d say that raising another $25 million from Meritech Capital Partners and with the participation of existing investors Lightspeed Venture Partners and Crosslink Capital is a good enough reason for DataStax to party.
DataStax will use the funds to further enhance its Big Data platform and increase the value for current customers while driving global customer acquisition.
Congrats to DataStax and Cassandra community!
Original title and link: $25 Million in C Round for DataStax (©myNoSQL)
Wednesday, 21 March 2012
Cassandra + Hadoop + Solr and Sqoop and Log4j => DataStax Enterprise 2.0
The tl;dr version is: DataStax has announced
Cassandra + Hadoop + Solr on the same cluster plus Sqoop, Log4j, and workload provisioning = DataStax Enterprise 2.0
For the longer version, there are a couple of new things worth emphasizing in this release:
- Fully integrated enterprise search
- RDBMS data migration
- Snap-in application log ingestion
- improvements to OpsCenter
- Elastic workload provisioning
Let’s take these one by one:
Fully integrated enterprise search or Solr on top of Cassandra
Cassandra distribution model is strongly inspired by Amazon Dynamo being characterized by high availability, elasticity, and fault tolerance. Solr is the search platform built on top of Lucene. Over time people learned how to scale Solr, but current approaches are far from being simple or offering an out of the box experience. Taking the Solr protocol and indexing capabilities and putting those on top of the Cassandra architecture makes a lot of sense.
Actually this has already been done in the form of Solandra (nb Solr integration in DataStax Enter. 2.0 is not based on Solandra though). For a scalable search solution there’s already ElasticSearch, but for someone running a Cassandra cluster, this looks like a useful addition to the stack.
DataStax has already showed this direction with what was called initially Brisk (or Brangelina for friends): Hadoop on top of the Cassandra cluster that became DataStax Enterprise 1.0. Solr on top of Cassandra is 2.0, but what will be the 3.0?
There are two cherries on top of this integration of Solr: easy index rebuild operations and CQL (Cassandra Query Language) access. I’ve seen XQuery translated to Lucene searches before, but I still need to see a SQL-like language translation.
As I’ve learned from Riak at Clipboard: Why Riak and How We Made Riak Search Faster, there is some complexity involved in scaling multi-matching search queries with term-based partitioning. Cassandra uses two partitioning strategies: random and order-preserving. It would be interesting to hear what partitioning strategy is used for Solr indexes. Update: I’ve got some answers so there’ll be a follow up with more details.
RDBMS data migration: it must be Sqoop
Nothing special here. You have a DataStax Enterprise cluster with some Hadoop nodes defined and you need to process data. But some of it lives in relational databases. Sqoop at rescue.
Snap-in application log ingestion: Flume or Scribe? No, it’s Log4j
When I read this bullet point my first thought was this is Flume. Or maybe Scribe. But most probably Flume. It looks like DataStax went a different route and offers log ingestion using Log4j. It’s true that Log4j or one of its flavors most probably exist in every Java project, but it still feels like an odd choice. On the other hand there’s a Cassandra plugin for Flume.
OpsCenter Enterprise 2.0
The OpsCenter is the management, monitoring, and control tool for DataStax Enterprise. The new version includes pretty much what you’d expect from an admin/monitoring tool:
- multi-cluster monitoring
- visual backup
- search monitoring
Looking back at the NoSQL administration/monitoring tools I’ve seen lately, I’m pretty sure I’ve identified a trend: they all come in various shades of black.
DataStax OpsCenter Enterprise:


Elastic workload provisioning
I’ve left at the end the feature that got me most interested into: elastic workload provisioning.
To better understand what this is, I had to go back to DataStax Enterprise 1.x where a node could be either a Cassandra node (OLTP) or a Hadoop node (processing). The new version allows quasi-dynamic node provisioning by changing the mode of a cluster (between Hadoop, Cassandra, Solr) with a stop/start operation. So given a cluster one could adjust its capacity and performance for different workloads (e.g. time-sensitive applications or temporary cluster operations).
Workload management is a feature present in most of the commercial data warehouse solutions. Even if in the very early days, DataStax Enterprise’s workload provisioning is the first take towards workload management in the NoSQL space.
Original title and link: Cassandra + Hadoop + Solr and Sqoop and Log4j => DataStax Enterprise 2.0 (©myNoSQL)
Monday, 19 March 2012
Big Data Market Analysis: Vendors Revenue and Forecasts
I think this is the first extensive Big Data report I’m reading that includes enough relevant and quite exhaustive data about the majority of players in the Big Data market, plus some captivating forecasts.
As of early 2012, the Big Data market stands at just over $5 billion based on related software, hardware, and services revenue. Increased interest in and awareness of the power of Big Data and related analytic capabilities to gain competitive advantage and to improve operational efficiencies, coupled with developments in the technologies and services that make Big Data a practical reality, will result in a super-charged CAGR of 58% between now and 2017.

While there are many stories behind these numbers and many things to think about, here is what I’ve jotted down while studying the report:
- it’s no surprise that “megavendors” (IBM, HP, etc.) account for the largest part of today’s Big Data market revenue
- still, the revenue ratio of pure-players vs megavendors feels quite unbalanced: $311mil out of $5.1bil
- the pure-player category includes: Vertica, Aster Data, Splunk, Greenplum, 1010data, Cloudera, Think Big Analytics, MapR, Digital Reasoning, Datameer, Hortonworks, DataStax, HPCC Systems, Karmasphere
- there are a couple of names that position themselves in the Big Data market that do not show up in anywhere (e.g. 10gen, Couchbase)
- this could lead to the conclusion that the companies that include hardware in their offer benefit of larger revenues
- I’m wondering though what is the margin in the hardware market segment. While not having any data at hand, I think I’ve read reports about HP and Dell not doing so well due exactly to lower margins
- see bullet point further down about revenue by hardware, software, and services
- this could explain why so many companies are trying their hand at appliances
- by looking at the various numbers you can see that those selling appliances usually have a large corporation behind supporting the production costs for hadware and probably the cost of the sales force
- in the Big Data revenue by vendor you can find quite a few well-known names from the consulting segment
- the revenue by type pie lists services as accounting for 44%, hardware for 31%, and software for 13% which might give an idea of what makes up the megavendors’ sales packages
- most of the NoSQL database companies and Hadoop companies are mostly in the software and services segment
Great job done by the Wikibon team.
Original title and link: Big Data Market Analysis: Vendors Revenue and Forecasts (©myNoSQL)
via: http://wikibon.org/wiki/v/Big_Data_Market_Size_and_Vendor_Revenues
Saturday, 25 February 2012
Cassandra as the Central Nervous System of Your Distributed Systems with Joe Stein - Powered by NoSQL
In the 4th week of the DataStax’s Cassandra NYC 2011 video series, we have Joe Stein from Medialets talking about the architecture
Before diving into the video here are some interesting data points:
- Medialets serves rich media ads
- they handle 3-4TB of daily data
- microsecond-level response times
- Cassandra is used for time series and aggregate metrics
- all MapReduce jobs written in Python. This reminded me of the recent post about the performance impact of operations in Hadoop Map phase
-
Medialets architecture:

-
Major components of the Medialets’s architecture:
- Kafka
- MySQL
- Cassandra: 6 node cluster, 100k requests, single DC
- Hadoop
- ZooKeeper: coordinates all the services on the platform
- some of the data in MySQL is replicated in Cassandra (and coordinated with ZooKeeper)
- data is fed back to MySQL
- Kafka for collecting analytics data:
- aggregates go into Cassandra
- events in Hadoop
- GROUP BY with Cassandra
- for real-time systems aggregations must be done upfront
- the way data is segmented is critical
- aggregation leads to data explosion
Sunday, 19 February 2012
Cassandra at Clearspring with Chris Burroughs - Powered by NoSQL
For today’s Powered by Cassandra video from the Cassandra NYC 2011 event organized by DataStax, I chose Chris Burroughs’s presentation about Clearspring’s usage of Cassandra. Just in case you wonder what Clearspring is doing, the sharing buttons you see here on myNoSQL are powered by AddThis product from Clearspring.
Saturday, 18 February 2012
Cassandra 101 for System Administrators with Nathan Milford - Powered by NoSQL
While today was supposed to be a new educational video from the Cassandra NYC 2011 video series, I thought that learning from the lessons of operating Cassandra at Outbrain to serve over 30 billion impressions monthly will be quite educational.
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