5 ms·

> If open source makes little effort to optimize the vast majority of other operational costs at scale, and this is largely the case in my experience I feel th

> If open source makes little effort to optimize the vast majority of other operational costs at scale, and this is largely the case in my experience I feel the opposite is true. There are many open source projects that are at least on par with their proprietary counterparts. Postgres is competitive with every SQL DB I've heard of except maybe in some niche use-cases. Redis is open source and incredibly performant. Same with Kafka (if you use it well). Linux sure runs better than Windows in my experience. There is also a whole class of open-source libraries like React that have taken over. I can't even think of a proprietary frontend framework. What software are you thinking of when you make these claims?

0xFACEFEED 7y ago
Not the parent but I thought of AWS services like RDS and S3. I believe the point being made was the money you save on licensing fees are insignificant compared to the amount you spend on paying people to maintain your infrastructure.
pjmlp 7y ago
I have used Postres during 4 years, Oracle and SQL server since 2000. Postgres is a nice database, but there are enterprise deployment use cases that it doesn't cover, which might be consired a niche, fair enough. What I don't consider a niche use case, is that its development tooling, meaning graphical DB management, graphical debugging of stored procedures, data modeling tooling, or integration of language runtimes into the database are all a bit behind of what those big DBs are capable of.
jandrewrogers 7y ago
There are two major dimensions to the operational cost weaknesses of open source. Neither is guaranteed to be meaningfully exploited by proprietary software in any particular case. Since we are talking about operational costs, this is almost entirely about data infrastructure software, not things like React. First, there is a vast amount of supported operational tooling that is simply missing from open source ecosystems. PostgreSQL, which I still use extensively, is a perfect example of this. The code bases around this tooling are several times the size of the product they support, and it isn't the kind of code that most developers aspire to write despite its high value to the customer. Oracle and SQL Server have architectures that are as obsolete as PostgreSQL, they don't compete on the basis of being modern, efficient designs but on the basis of having dramatically better operational tooling. Cloud RDBMS attack a different aspect of this. Second, is the operational infrastructure costs i.e. how much hardware is required to run a given workload. This is the larger threat to open source, particularly as the data intensity of business increases. PostgreSQL, Kafka, and Redis (I've used all three operationally) have several times the hardware requirements to deliver a workload in practice than is required with a state-of-the-art architecture. This isn't hypothetical, I've designed engines that replaced them when warranted. An 80% reduction in infrastructure cost is attractive when you are already spending tens or hundreds of millions of dollars per year on it. Some popular proprietary software is just as inefficient but that isn't guaranteed to remain the case (and I've replaced those systems too). Designing efficient software architecture isn't magic (see: ScyllaDB), you simply see very few examples of it in open source because it isn't a priority (see: use of managed languages for data infrastructure despite this being a known limitation). The reality is that I can guarantee data intensive businesses who make competent use of open source that I can reduce their infrastructure costs by 4x with ease. You can bury a massive amount licensing and engineering costs in those savings. Also, some companies are explicitly looking at this as a major "green" initiative. The wasteful infrastructure footprint to deliver a workload with open source is viewed as environmentally unfriendly, and this is pushing companies to consider proprietary solutions even if they are not sensitive to operational costs. That isn't a conversation open source is currently prepared to have but it is coming.
- exceptione 7y ago
  > I can guarantee data intensive businesses who make competent use of open source that I can reduce their infrastructure costs by 4x with ease I am interested in your perspective and experiences. > Oracle and SQL Server have architectures that are as obsolete as PostgreSQL, they don't compete on the basis of being modern, efficient designs but on the basis of having dramatically better operational tooling. What dramatically better tooling does SQL Server has? > PostgreSQL, Kafka, and Redis (I've used all three operationally) have several times the hardware requirements to deliver a workload in practice than is required with a state-of-the-art architecture. What should I think of when you talk about state-of-the-art architecture? And what would replace aforementioned tools? What should the open source offerings do to win you over?
  - wayneftw 7y ago
    > What dramatically better tooling does SQL Server has? I don't know about Oracle but SQL Server Data Tools (SSDT) and SQL Server Management Studio (SSMS) are vastly better than anything I've seen for open source databases. SSMS is just a really good visual client with an excellent table/view designer, diagram builder and query builder with GUI management features that let you manage virtually every facet of your server and databases. SSDT lets you treat your SQL schema, database settings and deployments like code, with versioning. All of your table schemas, views, functions, procedures, settings, seed data, etc. are stored as text in your git repo. When you're creating, it has excellent intellisense/autocomplete. You can use it to diff your schema and data against a given SQL Server database to generate migration scripts. You can also do data comparisons between your seed data and your server and you can diff schemas and data between 2 different servers without even having created an SSDT schema. Another very useful feature is that you can reverse engineer a SQL Server database that was already created in order to start your SSDT project. It also has visual designers for all of the aforementioned things. It used to be a separate tool, but now it's part of the free Visual Studio community edition. Both tools are free, as are various editions of SQL Server. Also, SQL Server itself has had features for a long time that PG is just starting to get such as real Stored Procedures, ones that can return multiple heterogeneous result-sets, run transactions and do control of flow with SQL-like statements (IF/THEN, DO, WHILE, etc.) It also has table variables, which are like in-memory tables, that you can use as a faster type of temp table for certain sets of data. Since I moved off of Windows for my workstations, I've been running SQL Server in Docker on Linux for the past few months - it's rock solid.

0xFACEFEED 7y ago

Not the parent but I thought of AWS services like RDS and S3. I believe the point being made was the money you save on licensing fees are insignificant compared to the amount you spend on paying people to maintain your infrastructure.

pjmlp 7y ago

I have used Postres during 4 years, Oracle and SQL server since 2000. Postgres is a nice database, but there are enterprise deployment use cases that it doesn't cover, which might be consired a niche, fair enough. What I don't consider a niche use case, is that its development tooling, meaning graphical DB management, graphical debugging of stored procedures, data modeling tooling, or integration of language runtimes into the database are all a bit behind of what those big DBs are capable of.

jandrewrogers 7y ago

There are two major dimensions to the operational cost weaknesses of open source. Neither is guaranteed to be meaningfully exploited by proprietary software in any particular case. Since we are talking about operational costs, this is almost entirely about data infrastructure software, not things like React. First, there is a vast amount of supported operational tooling that is simply missing from open source ecosystems. PostgreSQL, which I still use extensively, is a perfect example of this. The code bases around this tooling are several times the size of the product they support, and it isn't the kind of code that most developers aspire to write despite its high value to the customer. Oracle and SQL Server have architectures that are as obsolete as PostgreSQL, they don't compete on the basis of being modern, efficient designs but on the basis of having dramatically better operational tooling. Cloud RDBMS attack a different aspect of this. Second, is the operational infrastructure costs i.e. how much hardware is required to run a given workload. This is the larger threat to open source, particularly as the data intensity of business increases. PostgreSQL, Kafka, and Redis (I've used all three operationally) have several times the hardware requirements to deliver a workload in practice than is required with a state-of-the-art architecture. This isn't hypothetical, I've designed engines that replaced them when warranted. An 80% reduction in infrastructure cost is attractive when you are already spending tens or hundreds of millions of dollars per year on it. Some popular proprietary software is just as inefficient but that isn't guaranteed to remain the case (and I've replaced those systems too). Designing efficient software architecture isn't magic (see: ScyllaDB), you simply see very few examples of it in open source because it isn't a priority (see: use of managed languages for data infrastructure despite this being a known limitation). The reality is that I can guarantee data intensive businesses who make competent use of open source that I can reduce their infrastructure costs by 4x with ease. You can bury a massive amount licensing and engineering costs in those savings. Also, some companies are explicitly looking at this as a major "green" initiative. The wasteful infrastructure footprint to deliver a workload with open source is viewed as environmentally unfriendly, and this is pushing companies to consider proprietary solutions even if they are not sensitive to operational costs. That isn't a conversation open source is currently prepared to have but it is coming.

exceptione 7y ago
> I can guarantee data intensive businesses who make competent use of open source that I can reduce their infrastructure costs by 4x with ease I am interested in your perspective and experiences. > Oracle and SQL Server have architectures that are as obsolete as PostgreSQL, they don't compete on the basis of being modern, efficient designs but on the basis of having dramatically better operational tooling. What dramatically better tooling does SQL Server has? > PostgreSQL, Kafka, and Redis (I've used all three operationally) have several times the hardware requirements to deliver a workload in practice than is required with a state-of-the-art architecture. What should I think of when you talk about state-of-the-art architecture? And what would replace aforementioned tools? What should the open source offerings do to win you over?
- wayneftw 7y ago
  > What dramatically better tooling does SQL Server has? I don't know about Oracle but SQL Server Data Tools (SSDT) and SQL Server Management Studio (SSMS) are vastly better than anything I've seen for open source databases. SSMS is just a really good visual client with an excellent table/view designer, diagram builder and query builder with GUI management features that let you manage virtually every facet of your server and databases. SSDT lets you treat your SQL schema, database settings and deployments like code, with versioning. All of your table schemas, views, functions, procedures, settings, seed data, etc. are stored as text in your git repo. When you're creating, it has excellent intellisense/autocomplete. You can use it to diff your schema and data against a given SQL Server database to generate migration scripts. You can also do data comparisons between your seed data and your server and you can diff schemas and data between 2 different servers without even having created an SSDT schema. Another very useful feature is that you can reverse engineer a SQL Server database that was already created in order to start your SSDT project. It also has visual designers for all of the aforementioned things. It used to be a separate tool, but now it's part of the free Visual Studio community edition. Both tools are free, as are various editions of SQL Server. Also, SQL Server itself has had features for a long time that PG is just starting to get such as real Stored Procedures, ones that can return multiple heterogeneous result-sets, run transactions and do control of flow with SQL-like statements (IF/THEN, DO, WHILE, etc.) It also has table variables, which are like in-memory tables, that you can use as a faster type of temp table for certain sets of data. Since I moved off of Windows for my workstations, I've been running SQL Server in Docker on Linux for the past few months - it's rock solid.