I have a data intensive project for which I wrote the code recently, the data and sp live in a MS SQL db. My initial estimate is that the db will grow to 50TB, then it will become fairly static in growth. The final application will perform lots of row level look ups and readings, with a very small percentile of db write backs.
With the above scenario in mind, its being suggested that I should look at a NoSQL option in order to scale to the large load of data and transactions, and after a bit of research the roads leads to Neo4j (while considering MongoDB as a second alternative)
I would appreciate your guidance with the following set of initial questions:
-Does Neo4j support the concept of store procs? and does it supports conditional statements (if then, else, loops, etc)?
-Would I be able to install and run the 50TB db on a single node (single Windows Server)?
-Does Neo4j support/leverage multiple CPUs in single server (ex: 4 CPUs)?
-Would open source version be able to support the 50TB db? or would I need to purchase the ENT version?
Regards,
-r
Related
I'm currently working on a project that needs to store data of about 5 to 10 entities and at most 5000 records for each of them.
I was thinking about using mysql or postgres or even mongodb but all of them seems to be a lot for this little data
What I'm looking for is a database that can query this little amount of data but frequently
Any suggestions?
Use SQLite DB
SQLite is a lightweight C library that provided a relational database storage engine. Everything in this database lives in a single file that you can put anywhere in your filesystem. And that’s all you need to use it!
Useful features
Full support for transactions, with COMMIT, ROLLBACK, and BEGIN.
Support for 32,000 columns per table JSON support 64-way JOIN support
Subqueries
Full-text search
Maximum database size of 140
terabytes! Maximum row size of 1 gigabyte! 35% faster than file I/O
I am working on a solution architecture and am having hard time choosing between Azure SQL DB or SQL DW.
The current scope involves around developing real-time BI reporting solution which is based on multiple sources. But in the long run the solution may be extended into a full fledged EDW and Marts.
I initially thought of using SQL DW so that for future scope the MPP capabilities could be used. But when I spoke to a mate who recently used SQL DW, he explained that the the development in SQL DW is not similar to SQL DB.
I have worked previously on Real Time reporting with no scope for EDW and we successfully used SQL DB. With this as well we can create Facts and Dimension and Marts.
Is there a strong case where I should be choosing SQL DW over SQL DB?
I think the two most important data points you can have here is the volume of data you're processing and the number of concurrent queries that you need to support. When talking about processing large volume data, and by large, I mean more than 3tb (which is not even really large, but large enough), then Azure SQL Data Warehouse becomes a juggernaut. The parallel processing is simply amazing (it's amazing at smaller volumes too, but you're paying a lot of money for overkill). However, the one issue can be the simultaneous query limit. It currently has a limit of 128 concurrent queries with a limit of 1,000 queries queued (read more here). If you're using the Data Warehouse as a data warehouse to process large amounts of data and then feed them into data marts where the majority of the querying takes place, this isn't a big deal. If you're planning to open this to large volume querying, it quickly becomes problematic.
Answer those two questions, query volume and data volume, and you can more easily decide between the two.
Additional factors can include the issues around the T-SQL currently supported. It is less than traditional SQL Server. Again, for most purposes around data warehousing, this is not an issue. For a full blown reporting server, it might be.
Most people successfully implementing Azure SQL Data Warehouse are using a combination of the warehouse for processing and storage and Azure SQL Database for data marts. There are exceptions when dealing with very large data volumes that need the parallel processing, but don't require lots of queries.
The 4 TB limit of Azure SQL Database may be an important factor to consider when choosing between the two options. Queries can be faster with Azure SQL Data Warehouse since is a MPP solution. You can pause Azure SQL DW to save costs with Azure SQL Database you can scale down to Basic tier (when possible).
Azure SQL DB can support up to 6,400 concurrent queries and 32k active connections, where Azure SQL DW can only support up to 32 concurrent queries and 1,024 active connections. So SQL DB is a much better solution if you are using something like a dashboard with thousands of users.
About developing for them, Azure SQL Database supports Entity Framework but Azure SQL DW does not support it.
I want also to give you a quick glimpse of how both of them compare in terms of performance 1 DWU is approximately 7.5 DTU (Database Throughput Unit, used to express the horse power of an OLTP Azure SQL Database) in capacity although they are not exactly comparable. More information about this comparison here.
Thanks for you responses Grant and Alberto. The responses have cleared a lot of air to make a choice.
Since, the data would be subject to dash-boarding and querying, I am tilting towards SQL Database instead of SQL DW.
Thanks again.
Introduction:
Hi, we use SQL Server 2016 Servers for App DBs (437 Applications) in our corporation. We have other environments (Such as HCM etc.,) from which data has to be available for these applications.
To meet this requirement, we have a shared DB with name CentralRepository to which data flows from other environments and make it available for these DBs.
Problem Description:
Now we are trying to migrate few of the critical applications(26) to Azure servers. Hence, we have to move the CentralRepository as well to make sure the necessary data is available for the applications. But moving the whole DB is waste of resources as we don't require the tables necessary for rest 410 DBs. Hence, we are planning to move the data necessary for these 26 applications i.e., around 110+ tables out of hundreds of tables.
I would like to know if there is any way we can do that other than using Import/Export Wizard (tough to move 110 tables data to all the Azure environments) or complete DB restoration (as it is relatively very huge DB).
It would be very helpful, if you can suggest work around this problem. Thanks in advance :)
I'm currently running an instance of MS SQL Server 2014 (12.1.4100.1) on a dedicated machine I rent for $270/month with the following specs:
Intel Xeon E5-1660 processor (six physical 3.3ghz cores +
hyperthreading + turbo->3.9ghz)
64 GB registered DDR3 ECC memory
240GB Intel SSD
45000 GB of bandwidth transfer
I've been toying around with Azure SQL Database for a bit now, and have been entertaining the idea of switching over to their platform. I fired up an Azure SQL Database using their P2 Premium pricing tier on a V12 server (just to test things out), and loaded a copy of my existing database (from the dedicated machine).
I ran several sets of queries side-by-side, one against the database on the dedicated machine, and one against the P2 Azure SQL Database. The results were sort of shocking: my dedicated machine outperformed (in terms of execution time) the Azure db by a huge margin each time. Typically, the dedicated db instance would finish in under 1/2 to 1/3 of the time that it took the Azure db to execute.
Now, I understand the many benefits of the Azure platform. It's managed vs. my non-managed setup on the dedicated machine, they have point-in-time restore better than what I have, the firewall is easily configured, there's geo-replication, etc., etc. But I have a database with hundreds of tables with tens to hundreds of millions of records in each table, and sometimes need to query across multiple joins, etc., so performance in terms of execution time really matters. I just find it shocking that a ~$930/month service performs that poorly next to a $270/month dedicated machine rental. I'm still pretty new to SQL as a whole, and very new to servers/etc., but does this not add up to anyone else? Does anyone perhaps have some insight into something I'm missing here, or are those other, "managed" features of Azure SQL Database supposed to make up the difference in price?
Bottom line is I'm beginning to outgrow even my dedicated machine's capabilities, and I had really been hoping that Azure's SQL Database would be a nice, next stepping stone, but unless I'm missing something, it's not. I'm too small of a business still to go out and spend hundreds of thousands on some other platform.
Anyone have any advice on if I'm missing something, or is the performance I'm seeing in line with what you would expect? Do I have any other options that can produce better performance than the dedicated machine I'm running currently, but don't cost in the tens of thousand/month? Is there something I can do (configuration/setting) for my Azure SQL Database that would boost execution time? Again, any help is appreciated.
EDIT: Let me revise my question to maybe make it a little more clear: is what I'm seeing in terms of sheer execution time performance to be expected, where a dedicated server # $270/month is well outperforming Microsoft's Azure SQL DB P2 tier # $930/month? Ignore the other "perks" like managed vs. unmanaged, ignore intended use like Azure being meant for production, etc. I just need to know if I'm missing something with Azure SQL DB, or if I really am supposed to get MUCH better performance out of a single dedicated machine.
(Disclaimer: I work for Microsoft, though not on Azure or SQL Server).
"Azure SQL" isn't equivalent to "SQL Server" - and I personally wish that we did offer a kind of "hosted SQL Server" instead of Azure SQL.
On the surface the two are the same: they're both relational database systems with the power of T-SQL to query them (well, they both, under-the-hood use the same DBMS).
Azure SQL is different in that the idea is that you have two databases: a development database using a local SQL Server (ideally 2012 or later) and a production database on Azure SQL. You (should) never modify the Azure SQL database directly, and indeed you'll find that SSMS does not offer design tools (Table Designer, View Designer, etc) for Azure SQL. Instead, you design and work with your local SQL Server database and create "DACPAC" files (or special "change" XML files, which can be generated by SSDT) which then modify your Azure DB such that it copies your dev DB, a kind of "design replication" system.
Otherwise, as you noticed, Azure SQL offers built-in resiliency, backups, simplified administration, etc.
As for performance, is it possible you were missing indexes or other optimizations? You also might notice slightly higher latency with Azure SQL compared to a local SQL Server, I've seen ping times (from an Azure VM to an Azure SQL host) around 5-10ms, which means you should design your application to be less-chatty or to parallelise data retrieval operations in order to reduce page load times (assuming this is a web-application you're building).
Perf and availability aside, there are several other important factors to consider:
Total cost: your $270 rental cost is only one of many cost factors. Space, power and hvac are other physical costs. Then there's the cost of administration. Think work you have to do each patch Tuesday and when either Windows or SQL Server ships a service pack or cumulative update. Even if you don't test them before rolling out, it still takes time and effort. If you do test, then there's a second machine and duplicating the product instance and workload for test.
Security: there is a LOT written about how bad and dangerous and risky it is to store any data you care about in the cloud. Personally, I've seen way worse implementations and processes on security with local servers (even in banks and federal agencies) than I've seen with any of the major cloud providers (Microsoft, Amazon, Google). It's a lot of work getting things right then even more work keeping them right. Also, you can see and audit their security SLAs (See Azure's at http://azure.microsoft.com/en-us/support/trust-center/).
Scalability: not just raw scalability but the cost and effort to scale. Azure SQL DB recently released the huge P11 edition which has 7x the compute capacity of the P2 you tested with. Scaling up and down is not instantaneous but really easy and reasonably quick. Best part is (for me anyway), it can be bumped to some higher edition when I run large queries or reindex operations then back down again for "normal" loads. This is hard to do with a regular SQL Server on bare metal - either rent/buy a really big box that sits idle 90% of the time or take downtime to move. Slightly easier if in a VM; you can increase memory online but still need to bounce the instance to increase CPU; your Azure SQL DB stays online during scale up/down operations.
There is an alternative from Microsoft to Azure SQL DB:
“Provision a SQL Server virtual machine in Azure”
https://azure.microsoft.com/en-us/documentation/articles/virtual-machines-provision-sql-server/
A detailed explanation of the differences between the two offerings: “Understanding Azure SQL Database and SQL Server in Azure VMs”
https://azure.microsoft.com/en-us/documentation/articles/data-management-azure-sql-database-and-sql-server-iaas/
One significant difference between your stand alone SQL Server and Azure SQL DB is that with SQL DB you are paying for high levels of availability, which is achieved by running multiple instances on different machines. This would be like renting 4 of your dedicated machines and running them in an AlwaysOn Availability Group, which would change both your cost and performance. However, as you never mentioned availability, I'm guessing this isn't a concern in your scenario. SQL Server in a VM may better match your needs.
SQL DB has built in availability (which can impact performance), point in time restore capability and DR features. You have the option to scale up / down your DB based on your usage to reduce the cost. You can improve your query performance using Global query (shard data). SQl DB manages auto upgrades and patching and greatly improves the manageability story. You may need to pay a little premium for that. Application level caching / evenly distributing the load, downgrading when cold etc. may help improve your database performance and optimize the cost.
We have a windows MFC app that is written against an access database on a company server. The db is not that big: 19 MB. There are at most 2-3 users accessing it at any one time. It is used in a factory environment where access speed (or lack thereof) over the intranet becomes noticeable as it is part of the manufacturing time for our widgets.
The scenario is this: as each widget is completed, it gets a record in the db.. by the end of the year, the db is larger and searching for a record takes longer and longer. The solution so far has been to manually move older records to an archival table about once a year.
We are reworking other portions of this app right now, and it would be a good time to move to another db if we are going to do it.
It is my understanding that if we were using sql, the search time would not go up as the table gets bigger because the entire .mdb does not have to be sent over the network each time. Is this correct? Does anyone have any insight about whether it could be worth it to go to the trouble (time and money) of migrating to a new db, or should I just add more functionality to the application we have now, and maybe automatically purge the older records from time to time, and add additional facilities to the app to get at the older records when needed?
Thanks for any wisdom you can share..
Since your database is small and very few users, I could not make a solid case for migration. I would definetly set up an script to archive old records on a more frequent basis (don't archive into same db, this would somewhat defeat the purpose).
But also make sure two things are correct as well.
INDEXES. If your queries start slowing down, make sure you have proper indexes
http://support.microsoft.com/kb/304272
Your network connection between computers is fast. Maybe upgrade to gigabit cards and router? Possibly put the db on a scsi drive (raid 10 for speed and redundancy)
Throwing advanced technology at simple problems is an expensive way to go and not always the answer!
First of all, the information that the whole table and the whole database is transferred across the network is simply incorrect. If the queries are indexed, then the search times should not go up that much over time.
As others have mentioned spending the time + money to setup and maintain and then have someone maintain and manage and support that database server is certainly a possibility here. However, keep in mind that simply migrating a JET based application to sql server in many cases will run slower, and in fact sql server is slower then JET when no network is involved.
So, I would take some time to ascertain why things slow down so much, and also check into how indexing is setup.
So, just keep in mind that it is pure folklore and myth that the whole tables and whole database is transferred over the network. This concept is ONLY DUE to most people really not having any computer training and not knowing and understanding how the JET data engine works.
I would probably move to either Microsoft SQL Server 2008 R2 Express Edition (free) or MySQL (free) if there is both funding and time to put in a data access layer. Because you will be making requests of a remote server and not operating on data at the local workstation this move is very involved from the development standpoint.
However you should analyze whether or not its more cost effective to perform your archival process quarterly or monthly, and just move the archive database to SQL Server 2008 R2 Express Edition. (You can install the Microsoft SQL Server Management Studio client tools on workstations and query the archival database for faster reports on historical data without rewriting your entire production application; similar solutions exist for using MySQL or other OSS/free RDBMS).
I have cilents with 300 mb databases although they should be upsizing to SQL Server for other reasons. 19 Mb is relatively small. If performance is bad enough that archiving speeds things up then check the indexes to the tables for all your sorting and selection fields. Albert gave you a good URL there to check.
Entire MDB files do not go down the wire. Unless you are missing indexes.
Instead of shipping the DB over the network to the client and then performing queries, you could instead write a small wrapper on the server that handles requests, looks up the result in the Access DB (using SQL + the Access ODBC driver), and returns the result. This avoids the overhead of a large migration you might not need and still gets rid of the basic problem the users are experiencing.
Moving to a "proper" database solution is the best long term solution, but if your needs scale linearly and slowly over the next 30 years, it's hard to justify an expensive migration. That said, if you expect to really ramp up, or want to be more "future-proof", migrating now will likely save money/time.
It is my understanding that if we were
using sql, the search time would not
go up as the table gets bigger because
the entire .mdb does not have to be
sent over the network each time. Is
this correct?
This general idea is true for almost all databases. The idea of a database is to separate your application from the actual data. The data resides in a database server. Your application doesn't.
Does anyone have any insight about
whether it could be worth it to go to
the trouble (time and money) of
migrating to a new db
Yes. Having proposed this many times. It's expensive. It's complicated. Your MS-Access database will never get better or faster.
Other database servers will (and can) get faster and more sophisticated. After all, you're not sending .MDB files through a network anymore. The limitations are reduced. You're working with standard SQL through ODBC. Any database will work at the end of ODBC. You can fire vendors to find better, faster, cheaper products. Once you stop using Access you have choices.
Either stop using Access now or plan to suffer with it forever. And remake this decision every year until the end of time.