Skip to main content

Toad for Cloud Databases

Looking for a free(!) tool to connect to your Cloud databases? One of the tools I’ve been trying is Toad for Cloud Databases, a free SQL-based tool with the familiar look and feel of Toad, which enables users to use SQL(yes indeed SQL) with a set of  non-relational databases, including Hadoop (Hbase & Hive), Cassandra, MongoDB, SimpleDB, and Azure Table Services.

How does it work?

There are two key components to Toad for Cloud Databases:

  • Toad client: Use it to access Cloud/NoSQL databases via SQL statements.
  • Data Hub: It translates SQL statements submitted through the Toad client into a language understood by the Cloud database, and returns results in the familiar tabular row and column format.
Installation

You can download it from the following location(you’ll have to register first): http://toadworld.com/Freeware/ToadforCloudDatabasesFreeware/tabid/842/Default.aspx

Run the installer after downloading has completed.

Get started
  • Start the Toad for Cloud Databases client. Once the client is loaded you’ll see the Data Explorer on the left.

image

  • Right click on the Embedded Data Hub and choose Map Data Source…

image

  • The Map Data Source wizard is loaded. Specify a Data source name and choose the appropriate Data source type(we’ll choose Azure Table Services).

image

  • Specify the credentials to connect to your data source and click OK to complete this step.

image

  • The data source is added to the Tree view.

image

  • However before we can start doing something, we have to create a mapping first. Right click on the Mappable Objects and choose Map Multiple Tables…

image

  • The Map Tables screen is loaded. Select the Table you want to map and click OK.

image

  • The tool will create a Table for us and map all the found columns as can be seen in the Data Explorer Tree view.

image

  • Now we can right-click on the created table and start writing SQL by choosing Open SQL Editor.

image

  • A SQL Editor is opened and you can write and execute SQL statements.

image

  • That’s it!
Labels:

Popular posts from this blog

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME         ...
Read more

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...
Read more

VS Code Planning mode

After the introduction of Plan mode in Visual Studio , it now also found its way into VS Code. Planning mode, or as I like to call it 'Hannibal mode', extends GitHub Copilot's Agent Mode capabilities to handle larger, multi-step coding tasks with a structured approach. Instead of jumping straight into code generation, Planning mode creates a detailed execution plan. If you want more details, have a look at my previous post . Putting plan mode into action VS Code takes a different approach compared to Visual Studio when using plan mode. Instead of a configuration setting that you can activate but have limited control over, planning is available as a separate chat mode/agent: I like this approach better than how Visual Studio does it as you have explicit control when plan mode is activated. Instead of immediately diving into execution, the plan agent creates a plan and asks some follow up questions: You can further edit the plan by clicking on ‘Open in Editor’: ...
Read more