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NoSQL databases are challenging relational technologies by delivering the flexibility required of modern applications. But, which NoSQL database is best architected to handle performance demands of today’s workloads? Benchmarks recently run by End Point an independent database firm, stress-tested Apache Cassandra, HBase, MongoDB, and Couchbase on operations typical to real-world applications. Resu
Version 3.0.0 of the DataStax Node.js driver is now available with support for Apache Cassandra 3.0. The main focus for this release was to add support for the changes in the schema metadata introduced in Cassandra 3.0 that is used internally by the driver. Additionally, we exposed Materialized Views metadata information and introduced a new Index metadata API. We also made other improvements to t
For hands-on exercises that allow you to try out the CQL statements in this blog, check out the Queries lesson from the Cassandra Fundamentals learning series. While they share similar syntaxes, there are lots of differences between CQL and SQL. The reasons for these differences come mainly from the fact that Cassandra is dealing with distributed data and aims to prevent inefficient queries. One o
DataStax DocumentationLearn how to create solutions using Astra DB, Apache Cassandra® and DataStax Enterprise.
For more recent data modeling content, check out the sample data models in the Data Modeling By Example learning series, as well as our Data Modeling in Apache Cassandra® whitepaper. Picking the right data model is the hardest part of using Cassandra. If you have a relational background, CQL will look familiar, but the way you use it can be very different. The goal of this post is to explain the b
For more recent Cassandra data modeling content, check out our Data Modeling in Apache Cassandra® whitepaper. Basic rules of data modeling in Cassandra involve manually denormalizing data into separate tables based on the queries that will be run against that table. Currently, the only way to query a column without specifying the partition key is to use secondary indexes, but they are not a substi
NoSQL databases are designed to support cloud application requirements and overcome the scale, performance, data model and data distribution limitations of traditional relational databases (RDBMS’s). NoSQL explainedTo better understand NoSQL databases, let’s first take a look at their alternative: relational databases. The SQL programming language was designed as an easy way to query and modify re
Apache Cassandra Benchmarking: 4.0 Brings the Heat with New Garbage Collectors ZGC and Shenandoah Apache Cassandra 4.0 beta is the first version that supports JDK 11 and onwards. Latency is an obvious concern for Apache Cassandra® users and big hopes have been put into ZGC, the new low latency garbage collector introduced in JDK 11. It reached GA in JDK 14, which made us eager to evaluate how good
Here at Datastax, my fellow intern Daniel Chin and I built a 32 node DataStax Enterprise cluster running on Raspberry Pi’s! We are showcasing the always on, fault tolerant nature of Cassandra by letting anybody take down an entire data center with the press of a Big Red Button in our lobby. Being able to withstand a data center going down is not just an edge case, it is an absolute necessity for t
I recently wrote about how not to benchmark Cassandra and some of the principles involved in benchmarking Cassandra and other databases correctly. Let’s take a look at how to apply these to a benchmark done by Thumbtack Technology for Aerospike. First, the basics: this test was done on bare metal machines, with SSD disks. The benchmark report doesn’t make it entirely clear how load generation wa
Background When discussing the tradeoffs between availability and consistency, we say that a distributed system exhibits strong consistency when a reader will always see the most recently written value. It is easy to see how we can achieve strong consistency in a master-based system, where reads and writes are routed to a single master. However, this also has the unfortunate implication that the s
There are a number of ways to ingest preexisting data into a Cassandra cluster. The venerable and low-level BinaryMemtable interface was used in the early days, but it was quite difficult to use, and it's not even an option anymore. The json2sstable and sstableloader tools are very efficient, but setting up the procedure involves careful configuration and network considerations. The BulkOutputForm
Cassandra Anti-Patterns: Queues and Queue-like Datasets | Datastax Deletes in Cassandra Cassandra uses a log-structured storage engine. Because of this, deletes do not remove the rows and columns immediately and in-place. Instead, Cassandra writes a special marker, called a tombstone, indicating that a row, column, or range of columns was deleted. These tombstones are kept for at least the period
One of the notable features of Amazon's 2007 Dynamo paper was the use of vector clocks for conflict resolution. However, the two most prominent systems designed by engineers who worked on Dynamo -- Cassandra and DynamoDB -- both avoid the use of vector clocks in favor of finer-grained updates. To understand why, let's first look at the problem that vector clocks solve. Resolving conflicts with vec
Cassandra is an excellent fit for time series data, and it's widely used for storing many types of data that follow the time series pattern: performance metrics, fleet tracking, sensor data, logs, financial data (pricing and ratings histories), user activity, and so on. A great introduction to this topic is Kelley Reynolds' Basic Time Series with Cassandra. If you haven't read that yet, I highly r
Four years ago, well before starting DataStax, I evaluated the then-current crop of distributed databases and explained why I chose Cassandra. In a lot of ways, Cassandra was the least mature of the options, but I chose to take a long view and wanted to work on a project that got the fundamentals right; things like documentation and distributed tests could come later. 2012 saw that validated in a
The R project is taking over the data world. With a plethora of algorithms at your fingertips it's not hard to see why R is such a powerful data analysis tool. I was fortunate enough to work with some of the original developers of the then S-Engine at bell labs out of college and even managed to write a few CRAN packages. In fact the ROracle package is now shipped with Oracle's big data appliance
The Cassandra File System (CFS) is an HDFS compatible filesystem built to replace the traditional Hadoop NameNode, Secondary NameNode and DataNode daemons. It is the foundation of our Hadoop support in DataStax Enterprise. The main design goals for the Cassandra File System were to first, simplify the operational overhead of Hadoop by removing the single points of failure in the Hadoop NameNode. S
As we've worked towards 1.0 over the past year, Cassandra's performance has improved spectacularly. Compared to the current release this time in 2010, we've increased our write performance a respectable 40%. But the real area we wanted to focus on improving was read performance, which we succeeded in increasing a phenomenal 400%! Reads There are actually two different execution paths for reads in
Slides and Videos from Cassandra NYC 2011 will be posted here. Thanks to all that attended and we look forward to seeing you next year! Chris Burroughs (Clearspring) – Apache Cassandra at Clearspring (HD Video) David Weinstein (Adobe) – Cassandra at Adobe (HD Video) Drew Robb (SocialFlow) – Cassandra at Social Flow (HD Video) Ed Capriolo (m6d) – Cassandra in Online Advertising (Slides and HD Video
Technical insights and success stories on cutting-edge generative AI, vector search, and real-time data innovations.
By Andrew Llavore - July 18, 2011 Jonathan Ellis, CTO of DataStax and project chair for Apache Cassandra, keynoted at Cassandra SF 2011. Major accomplishments for the project in the last year include better support for multi-data center deployments, optimized read performance, included integrated caching and improved client APIs including a SQL-like language CQL. Read More
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DataStax EnterpriseDeliver Apps at Scale on Bare Metal or Kubernetes Deliver real-time apps and integrate vector database capabilities into your workloads with the scale-out, cloud native NoSQL database built on Apache Cassandra® and proven by the Fortune 100.
Spotlight InfoWorld Technology of the Year DataStax Enterprise has been named a 2019 InfoWorld Technology of the Year Read Now Overview In Cassandra 0.6, we created a ColumnFamilyInputFormat, allowing you to read data stored in Cassandra from a Hadoop mapreduce job. However, you had to write the output from these jobs to a local file or HDFS, or manually connect to Cassandra in your reducer to sto
Deprecation warning This post covers the obsolete Cassandra 0.7. Modern Cassandra manipulates indexes using CQL. Overview In Cassandra, indexes on column values are called "secondary indexes," to distinguish them from the index on the row key that all ColumnFamilies have. Secondary indexes allow querying by value and can be built in the background automatically without blocking reads or writes. Th
DATASTAX FOR DEVELOPERSLearn How to Succeed with Apache Cassandra® Build your next-generation applications with the NoSQL database that has proven high performance, linear scalability and zero downtime across on-premises, hybrid, and multi-cloud environments.
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