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1,067,472 Views • Dec 8, 2020 • Click to toggle off description
Behind-the-scenes, they use a keyspace to distribute your data across multiple servers or partitions. This allows them to scale horizontally across many thousand servers.
NoSQL databases can operate in multiple modes: as key-value store, document store or wide column store.
You can run your own NoSQL database with software like Cassandra, CouchDB, MongoDB or Scylla. You can also use a cloud version like AWS DynamoDB, Google Cloud BigTable or Azure CosmosDB.
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YouTube Comments - 579 Comments
Top Comments of this video!! :3
In SQL, you can also partition databases and it's called sharding. You can also duplicate your databases and it's master and slave databases
576 |
Thanks for this great simple and short explanation of data storage in NoSQL-databases. Exactly what I was looking for 🙂
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Relational databases can be way more efficient at acessing well structured data, as it is placed in predictable memory locations, and the relation keeping processing needed isn't comparable with the overhead a noSQL DB has at acessing data.
The choice of SQL vs noSQL really depends on the specific application, one isn't better than the other.
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In MySQL, you don't HAVE to use the relational structuring of your data. you can simply have multiple tables and treat them as truely separate tables where you run multiple queries to get all your data, each query runs on one table for example. Then you can kame the relations in your program if you need it.
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I feel like NoSQL is what you get when a coder creates a database that never learned to clean up his room or organize anything.
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"EVERYTHING OLD IS NEW AGAIN !"
What you are describing is also called an Indexed Sequential Access Method (ISAM) database/file. I believe it was invented by IBM in the 60s or 70s. This was long before relational database existed. Other types of databases existed but they were very complex and hard to program and maintain. In those days "management" want reports about what was n these data files. IBM invented software to "query" these file called Report Program Generator (RPG). It was easy to use and could be setup to do various queries quickly. It was supperseeded by RPG-II that lived on for many, many years.
Digital Equipment Corporation (DEC) had their own version that came out in the 70s on PDP-11 and VAX computer systems. It had its own querey/report generator language cal Datarieve. Datatieve was a bit query as it was both an interactive as well "fixed" report generator.
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You can store key value in relational database. And you can partition relational database to multiple servers based on primary key or something else. Relational db can do everything nosql can, but not the other way around
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There has been a style of database around since the late 1960’s that offers the best of both, plus many features that both SQL and NoSQL lack. It’s Pick and it’s many variants and descendants. Hashed, variable length, delimited, and it’s native programming language is a high-octane version of that old favorite, BASIC. It may not scale to Amazonian proportions, but it is great for most of the real world. The company I worked for started using it in 1996. By the time I retired in 2009, they had grown to over $100 million in annual sales and are still thriving on Pick clone Unidata.
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Now I got it. I took me a while to understand how does the nosql works. I've been working with SQL Server and MySQL for a few years so the nosql idea had confusing my brain a little bit lol. Thanks
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Teradata (since the 1980's) and IBM's DB2 Parallel Edition (since the mid-1990's) are examples of SQL databases that use sharding to scale horizontally in a linear fashion. Although both of these typically have more than just a key and a single value, they could be used with only one value (or one value in XML format) just like NoSQL databases, but they can also have multiple values.
The problem with Teradata and DB2 Parallel Edition is that the cost of license is significantly higher than NoSQL databases, which are typically open-source software with only support fee costs.
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2:50 is such a surprising random indian accent moment
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Thank you for a fantastic overview! Appreciate it, well done!
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just as nosql servers might have a sql layer, so have sql servers like postgres already the ability to partition or have dynamic data in json blobs (including a subset of sql to query it). not sure how powerful that is however compared.
also, your queries only double if you keep it in the pk range; otherwise they dont as each partition has to perform your query, i would suppose
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I've been using NoSql databases for a while but could never understand what the partition key was or how to use it, but your video has finally explained it, thanks!
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Excellent information and presentation. Thank you!
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@3:30 a hash is used rather than just the primary key's range directly because the hash will always partition evenly (i.e. the magnitude of the computed hash is randomly spread throughout the range)
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I have been doing this for over 30 years with relational db's. We have never used fixed foreign keys (db managed ones), but always done this ourselves inside the code. This means our relational db's have been stand alone tables (with indexing) since the start and all queries we do just link the keys to get the data. Still scaling is an issue, but we can split chop, remove data into archives/servers at will and the db doesnt break.
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Thanks bro, you've made it easy to understand.
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Thanks for explaining .Simple and to the point .Subscribed !
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@markrosenthal9108
3 years ago
This video incorrectly conflates query language with storage architecture. These concepts are independent of each other. Columnar, distributed storage provides most of the horizontal scaling discussed in this video. In today's leading distributed/columnar databases, the data can be accessed with either SQL or NoSQL depending on the access requirements of the application problem you need to solve while realizing the performance benefits of horizontal scaling.
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