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Transactional Replication vs. Change Tracking. Two new replication-ish features were introduced in SQL Server 2008: Change Tracking and Change Data Capture.Binky Is the i. Phone App for People Who Are Conflicted About Social Mediai. Phone: The only thing better than using social media is not using social media. That’s why there’s Binky, which is sort of both. Binky is an app that lets you go through the motions of social media (swiping on pictures, scrolling through pictures, commenting on pictures) without actually connecting with human beings. It’s an endless feed of pictures of things, from potato bread to Lynn Margulis. The app mixes features of all different social media like swiping right on things Tinder- style and re- binking binks (“Do you want to re- bink this bink? This doesn’t do anything.”). ![]() When you favorite a bink (which is what they call their posts), an explosion of stars appears. Congrats! It also gives you the illusion of choice by letting you type on a keyboard that generates comments with lots of hashtags and emoji like “so cool! Binky is just as meaningless as other social media apps, but it’s upfront about it,” said Binky creator Dan Kurtz to NPR. Sometimes it feels like it’s doing too much, like letting you swipe left and right on binks and also being able to comment and re- bink binks. But that’s sort of the point: it’s the fidget cube of social media, giving you content to mindlessly scroll through without you actually having to log onto social media. Sadly the app is only available on i. OS, but will soon roll out on Android. About Robert Pearman Robert Pearman is a UK based Small Business Server enthusiast. He has been working within the SMB IT Industry for what feels like forever. The app mixes features of all different social media like swiping right on things Tinder-style and re-binking binks (“Do you want to re-bink this bink? Query Hints should be used carefully, because they restrict the possible optimizations during the query compilation, and they may, later, force the optimizer to use. Introduction to SQL Server Transactional Replication. Repli- Roach. If SQL Server’s Transactional Replication was an animal, it would be a cockroach. It’s not pretty, but it’s resourceful and strong. Once you get even a small amount of replication in your environment it starts spreading everywhere. And if it gets out of control– well, in that case you’ve got no choice but to pretty much bomb everything, clear the fumes as quickly as possible, and reinitialize. But unlike a cockroach, you can’t always just get rid of Transactional Replication. The bad news is, it’s here to stay. In this post you’ll get a whirlwind introduction to Transactional Replication. I’ll explain why newer features like Change Tracking, Change Data Capture, and Availability Groups have failed at exterminating Transactional Replication. You’ll also learn what it takes to support replication in a mission critical environment. SQL Server Transactional Replication basics. Transactional Replication lets you publish and filter individual database objects. Publications define replicated articles. Transactional Replication lets you select individual tables to publish (called “articles”), allowing you to just publish a fraction of a very large database. It also lets you: 2) A fleet of SQL Server Agent jobs does magic. I just learned this: a group of cockroaches is called “an intrusion of cockroaches.” That seems like it probably applies to a whole lot of SQL Server Agent jobs, too. Exactly how many jobs? So many jobs that you’ll lose count. Replication is complicated. It’s got a SQL Server Agent job to read the transaction log of where you’ve defined your publications (Log Reader Agent). There’s another job that helps run Snapshots (it helps you initialize or re- initialize the replication). Another helps apply the snapshot and move transactions around (the Distribution Agent). There are also jobs for cleaning things up, refreshing monitoring, and all the general scuttling around that replication does. The distribution database collects commands. Replication doesn’t send transactions directly to your subscribers. The Log Reader Agent snoops in your transaction log and figures out what changes have been made to the articles you’ve defined in your publications. When it finds changes, it sends them over to the distribution database. You can configure distribution on the publishing server, or you can scale it out to an independent server. The important thing to know is that each change you make in your publisher gets translated into independent commands (insert, update, and delete), and these commands get inserted into the distribution database before it moves onward. No matter what you do, that process takes some time: replication isn’t instantaneous. Commands get applied to subscribers. You may set up many subscriptions to a single publication. This is part of what’s cool about replication– a single publication can publish a narrow group of tables to be read by many subscribers (perhaps in different datacenters around the world). You can elect to configure pull subscriptions or push subscriptions. In the “pull” model, each subscriber runs jobs that poll in data periodically. In the “push” model, the changes are more constantly pushed out to the subscribers from the distributor. Old commands get cleaned up. Hopefully. Lots of commands may collect up in the distribution database. That can be a good thing– maybe a subscriber is offline for a few hours, wouldn’t it be sad if it couldn’t catch up? But you don’t want to hoard too many commands, or your distribution database will bloat up like crazy. There are jobs that delete out old commands. In an active environment, balancing out cleanup, new activity, and pushing data to subscribers can be… challenging. Then you learn a million factoids. We’ve barely scratched the surface. I haven’t shown you Replication Monitor, a tool whose GUI is so confusing that you don’t dare take your eyes off it. It’s hard to avoid it, but do use it with care– I’ve had it cause blocking when run by multiple people concurrently in a couple versions of SQL Server.) I haven’t talked about tweaking Replication Agent Profile Settings or the limitations of tracer tokens. We haven’t debated when you might want to initialize from backup. Transactional Replication is a complicated monster. It’s not something you can book- learn, it’s just got far too many configuration options and moving parts. Replication something you learn by trying it, having problems, fixing it, and then repeating the process. Transactional Replication vs. Change Tracking. Two new replication- ish features were introduced in SQL Server 2. Change Tracking and Change Data Capture. These two technologies are both completely separate from replication, and from each other. Change Tracking, like transactional replication, is available in Standard Edition. That’s a good thing, but if you’re comparing the two features, people still pick replication. Change tracking just answers a very basic question: has a row changed? It doesn’t capture the “old data” or send the “new data” anywhere– it just updates a marker letting you know that a row has changed since your application last polled it. It’s up to the user to write an application to regularly poll the tables (and know what version it last tracked). It’s also recommended for the user to enable snapshot isolation on the database using change tracking and explicitly use it when querying Change Tracking tables to make sure that you don’t miss data or cause blocking with Change Tracking cleanup processes. Snapshot isolation is great, but turning it on and managing it are not at all trivial. Change Tracking also has some additional overhead. For each row modified in a tracked table, a row is added to a change table. For each transaction that commits, a row is inserted into an internal transaction table, also. It doesn’t keep the previous values in those tables, so they’re small inserts, but on super active tables that’s extra writes hitting the transaction log of your database– and extra writes when those tables get cleaned up.)Verdict: Replication is complicated, but Change Tracking ain’t simpler. Due to having much less custom code to write, more freedom with isolation levels, and no extra inserts in internal tables, most people decide that Transactional Replication beats Change Tracking. Transactional Replication vs. Change Data Capture. How about Change Tracking’s distant cousin, Change Data Capture? This is an Enterprise Edition feature– it must surely perform better than the Standard Edition friendly Transactional Replication, right? Well, sorry, not necessarily. I love the concept behind Change Data Capture. Imagine that you’re a database administrator managing a transactional replication publication. You have a table that holds advertising campaign keywords. Each row in the table contains a Campaign. ID column, a keyword column, and a Bid. Price column. Some campaigns have hundreds of thousands of keywords. Tools let advertisers set up campaigns quickly with LOADS of keywords– and the keyword Bid. Price. No magical creature here. It’s the day before a big holiday. One of the big advertisers goes in, and sets up a huge campaign– 2. K rows of changes roll into the table. They realize they messed up and deactivate it right away. K more changes roll in. Then they set up a new one. Then the tweak the Bid. Price. Suddenly replication is churning trying to get all these changes into the distribution database, not to mention handle what’s happening in any other replicated tables you have. Replicated commands start backing up. You’re left saying, “But all I want is the most recent change they made!”This is the scenario where Change Data Capture sounds like a great idea. The concept with “CDC” is that you write your own polling. If you poll every hour, you just pick up the latest version of the row (or whatever history you want), and take that with you. You don’t have to take every command, so it’s super light- weight. But CDC isn’t all unicorns and magic, either. When you enable Change Data Capture for a table, SQL Server starts tracking inserts, updates, and deletes in the transaction log (similarly to replication). But when you make changes, they’re read from the log and then inserted into “change tables” associated with the tracked tables. The change tables are automatically created in the same database as the tracked tables– and inserts into them are also logged operations.
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