By replacing independent, fragmented databases with a distributed system, banks can reduce data reconciliation costs while also improving data quality and ensuring data security.
Source: Blockchain Tech Could Save Banks $12 Billion A Year
It has become increasingly obvious in recent months that blockchain will be key to the future of the banking industry, with the majority of banks expected to adopt the technology within the next three years.
But before you embark on that shiny blockchain project, you need to have a very clear idea of why you are using a blockchain. There are a bunch of conditions that need to be fulfilled. And if they’re not, you should go back to the drawing board. Maybe you can define the project better. Or maybe you can save everyone a load of time and money, because you don’t need a blockchain at all.
Source: Avoiding the pointless blockchain project | MultiChain
Blockchains are a technology for shared databases.
Blockchains are a technology for databases with multiple writers.
blockchains are a technology for databases with multiple non-trusting writers.
The switch from relational hadn’t been too hard because Riak is a key-value store, which made modeling relatively easy. Key value-stores are relatively simple database management systems that store just pairs of keys and values.
McCaul reckoned, too, migration of data had been made possible because the structure of patient records lent themselves to Riak’s key-value mode
via NHS grows a NoSQL backbone and rips out its Oracle Spine • The Register.
The main tenets of the Unix Philosophy are as follows::
- Small is beautiful.
- Make each program do one thing well.
- Build a prototype as soon as possible.
- Choose portability over efficiency.
- Store data in flat text files.
- Use software leverage to your advantage.
- Use shell scripts to increase leverage and portability.
- Avoid captive user interfaces.
- Make every program a filter.
via Tenets of the UNIX Philosophy
You’ll learn how data is replicated within a cluster, how failover occurs, and the evolution of how his team decided to split data across a cluster of machines. Paul also touches on distributed consensus with Raft, replication fault tolerance with a write ahead log, and how we schedule frequent tasks to run in a reliable way across a cluster.
via The Distributed Database Internals of InfluxDB – open source software.
PostgreSQL’s structured format for saving JSON, called JSONB, eliminates the need for restructuring a document before it is committed to the database.
via New PostgreSQL guns for NoSQL market – Computerworld.
No matter how you slice it, the database market is massive and evolving. It’s also a market that has received a disproportionate share of VC investment, with VCs plowing funding into a long list of database related market segments including: NoSQL, Hadoop, graph databases, open-source SQL, cloud-based databases, visualization, etc. But for all of that innovation, the process of setting up and running very large database remains either expensive or complicated. Expensive because large databases still often require expensive hardware and/or licenses. Complicated because setting up a massive cluster of commodity machines to run a database requires a ton of administrative work and expertise that not a lot of people have. It’s this administrative complexity that Crate is out to eliminate – and that’s the real story behind the investment: the democratization of database cluster management. Crate’s real claim to fame is that it allows developers – any developer – to easily set up a massively scalable data store on commodity hardware with sub-second query latency simply and within minutes.
via Democratizing the Datastore: Why we invested in Crate | Yankee Sabra Limey.
And what about compatibility between MySQL and MariaDB? The MariaDB team works hard to continue with full compatibility with MySQL, and they continue to pull in bug fixes from the source. But the new features (and numbering scheme) suggest that, despite best efforts, the two platforms will increasingly diverge.
via MariaDB vs. MySQL: A Comparison.
During the class in the spring of 2012 he learned the graphics programming language CUDA, and that opened the doors for tweaking GPUs to divide advanced computations across the GPUs massively parallel architecture.
He knew he had something when he wrote an algorithm to connect millions of points on a map, joining the data together spatially. The performance of his GPU-based computations compared to the same operation done with CPU power on PostGIS, the GIS module for the open-source database PostgreSQL, was “mind-blowing,” he said.
via Fast Database Emerges from MIT Class, GPUs and Student’s Invention.