Sorry for the confusion. It's not opensource. For first few installs, we are offering free 3 months and free consulting service to setup the tool end to end at your org. Post that pricing will be based on AI tokens consumption with some standard monthly pricing (we are also exploring the pricing sweet spot)
I am happy to get connected over email venkat@deepsql.ai and share more details on pricing and deployment help.
The landing page doesn't show a link to your GitHub. Despite mentioning "self-hostable", I genuinely thought it was closed-sourced. I doubt first-time users will trust a random tool and grant it database-level access with a curl command.
Great point and thanks for the feedback. We made it self-hostable so that data doesn't leave the premises. We haven't open sourced the code yet, but most likely we will head in that direction very soon.
> 2. BI dashboards(we removed spend on tableau, retool and appsmith)
Can you explain this in more detail? You saying that DeepSQL can create BI dashboards that makes Tableau and friends redundant -- are you talking about analytics dashboards consumed by business teams or more like db ops dashboards used by backend teams? Does the user prompt the agent for them, or does it build dashboards that it infers are needed?
Deepsql has built in BI dashboards server - You can ask agent to build any BI dashboard from the connected data sources (this can be used by your internal teams or you can even share the dashboard link with customers with password protection, just like how we would share the retool links).
Deepsql doesn't replace your DBA, it gives your DBA super powers. In my org, when we had to decide on hiring a DBA, we chose building deepsql and empowered our senior engineer to handle the database tasks like a senior DBA.
We did cut our overall DB spend by more than 3x. Our $9K spend drops to $3k - indexes not kicking in, rapid growth of log tables and schema bloat were the culprits. Also, we removed the retool and appsmith licenses, another $2k savings.
We worked with 6 YC companies who are running on Aurora postgres and worked through the inefficiencies of workloads - too many indexes (in some cases almost every column is indexed), over indexing significantly increases I/O ops (writes), this hidden costs are enormous for fully managed services like Aurora. In all these cases, we could safely come up with a plan to cut down their DB spend by more than 40%.
Deepsql doesn't require any predefined rules + stats, nor you need a DBA to operate it. It's an autonomous agent, that learns your business context, schema, join relationships and creates a mental map of everything (just like a DBA who joined your team). This we call it deepsql brain init stage.
Once the init is done, it will then look at all slow queries workload, comes up with comprehensive suggestions of indexes, MVs etc. Other DBA tools might look at one query at a time, if we try to optimize one query at a time, we might over index.
Also, deepsql is intelligent in understanding the deployment type. Postgres standalone deployment is very different than Aurora postgres. Cost factors are quite different. Other DBA tools might ignore these factors - Hence they need well trained DBA to use them.
Is this an open source tool? Is it something we have to pay for? The site really doesn't tell me what I should be expecting.
Sorry for the confusion. It's not opensource. For first few installs, we are offering free 3 months and free consulting service to setup the tool end to end at your org. Post that pricing will be based on AI tokens consumption with some standard monthly pricing (we are also exploring the pricing sweet spot)
I am happy to get connected over email venkat@deepsql.ai and share more details on pricing and deployment help.
The landing page doesn't show a link to your GitHub. Despite mentioning "self-hostable", I genuinely thought it was closed-sourced. I doubt first-time users will trust a random tool and grant it database-level access with a curl command.
Great point and thanks for the feedback. We made it self-hostable so that data doesn't leave the premises. We haven't open sourced the code yet, but most likely we will head in that direction very soon.
> 2. BI dashboards(we removed spend on tableau, retool and appsmith)
Can you explain this in more detail? You saying that DeepSQL can create BI dashboards that makes Tableau and friends redundant -- are you talking about analytics dashboards consumed by business teams or more like db ops dashboards used by backend teams? Does the user prompt the agent for them, or does it build dashboards that it infers are needed?
Deepsql has built in BI dashboards server - You can ask agent to build any BI dashboard from the connected data sources (this can be used by your internal teams or you can even share the dashboard link with customers with password protection, just like how we would share the retool links).
Deepsql doesn't replace your DBA, it gives your DBA super powers. In my org, when we had to decide on hiring a DBA, we chose building deepsql and empowered our senior engineer to handle the database tasks like a senior DBA.
> cut database costs by 40%
Where does this number come from? It feels completely arbitrary.
We did cut our overall DB spend by more than 3x. Our $9K spend drops to $3k - indexes not kicking in, rapid growth of log tables and schema bloat were the culprits. Also, we removed the retool and appsmith licenses, another $2k savings.
We worked with 6 YC companies who are running on Aurora postgres and worked through the inefficiencies of workloads - too many indexes (in some cases almost every column is indexed), over indexing significantly increases I/O ops (writes), this hidden costs are enormous for fully managed services like Aurora. In all these cases, we could safely come up with a plan to cut down their DB spend by more than 40%.
This is an interesting product. Any comparison with other DBA tools? There are many tools can fix the slow queries, based on rule+statistics.
Deepsql doesn't require any predefined rules + stats, nor you need a DBA to operate it. It's an autonomous agent, that learns your business context, schema, join relationships and creates a mental map of everything (just like a DBA who joined your team). This we call it deepsql brain init stage. Once the init is done, it will then look at all slow queries workload, comes up with comprehensive suggestions of indexes, MVs etc. Other DBA tools might look at one query at a time, if we try to optimize one query at a time, we might over index.
Also, deepsql is intelligent in understanding the deployment type. Postgres standalone deployment is very different than Aurora postgres. Cost factors are quite different. Other DBA tools might ignore these factors - Hence they need well trained DBA to use them.
So, does it help with context management or so called MemoryBank setup?
Yes, it has built in storage layer(Postgres and PGVector)