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CData Drivers
Description de CData Drivers
Des connecteurs de données basés sur des standards pour les développeurs, les experts en données et bien d'autres encore, permettant un accès SQL à vos données via JDBC, ODBC, ADO.NET, Python, Power BI, Tableau, SSIS, Excel ou PowerShell. Travaillez avec des données en direct provenant de systèmes Big Data et NoSQL (Google BigQuery, Databricks, Snowflake, MongoDB, etc.) ; Marketing (Salesforce Pardot, HubSpot, Mailchimp, Marketo, etc.) ; Collaboration (SharePoint, Slack, Microsoft Teams, Trello, etc.) ; CRM (Customer Relationship Management) ERP (Enterprise Resource Planning) (Salesforce, SAP, Oracle NetSuite, Dynamics 365, etc.) ; API (Application Programming Interface) de fichiers (CSV, JSON, Parquet, XML, OData, REST, etc.) ; Comptabilité (QuickBooks Online, Dynamics, ADP, Xero, Sage Intacct, etc.) ; E-commerce (PayPal, Stripe, Shopify, WooCommerce, etc.) ; SGBDR (Azure Synapse, DB2, MySQL, PostgreSQL, SAP HANA, SingleStore, Amazon Redshift, etc.)
Qui utilise CData Drivers ?
Non fourni par l'éditeur
CData Drivers ne vous convainc pas tout à fait ?
Comparer avec une alternative populaire
CData Drivers
Alternatives à CData Drivers
Avis sur CData Drivers
Alternatives envisagées précédemment :
Robust Automation with CData Python Connectors
Commentaires : For smooth ORM Automation & DB-API purchases in on-premise relational databases, I would suggest Data Python Connectors. In addition, it may be utilized for unique business data-driven applications, data transformation, and data visualization because to its potent built-in SOL engine, which controls all code interpretations.
Avantages :
The vast range of code library functions provided by CData Python Connectors facilitates the automation of data transfer in relational databases. It enables me to create, read, update, and remove data and schema from the appropriate database by writing my application code in Python rather than SOL. I can easily work with Python, which is the biggest benefit of adopting CData Python Connectors in my firm. This provides a variety of features like dynamic execution, support for large libraries, portability across several platforms, and has large additions of third-party modules.
Inconvénients :
The CData Python Connectors' python-based API makes it simple to learn how the application is coded. Even those just getting started with object mapping may easily rearrange it to meet the needs. Quality and usability present no problems for me. So there is nothing wrong with it.
Alternatives envisagées précédemment :
Powerful Data Transform
Avantages :
A large amount of data access is available to connect with Excel and update data from live implementations
Inconvénients :
Cost wise is a small investment considering the benefits provided
Python
Commentaires : I have an overall good excperience with this product.
Avantages :
Its a very easy and intuitive programming software.
Inconvénients :
I fint it hard to export and import datasets.
My experience with CData Python Connectors
Commentaires : I am overall pleased with the product. However it would be great to be able to download python and work offline.
Avantages :
I like how easy it is to learn and operate.
Inconvénients :
I dislike the fact that you have to import specifick packages to use for instance basic mathematical symbols.
Easy to get started!
Commentaires : Its a required software in my curriculum.
Avantages :
Really user friendly. The UI is great and you can get started in 5 minutes. Great customer support!
Inconvénients :
It is a bit slow and that makes it difficult to use some times.
