22 Best Database As A Service Providers In 2024

Ninox provides a drag-and-drop interface that allows you to build custom database applications without any programming expertise.

Why I picked Ninox: What impresses me about Ninox is that it comes with various database template options. For example, HR teams can use their leave planners, onboarding and offboarding catalogs, and time-tracking template. Admin teams can use inventory, contracts, and software license templates. More templates are available for ERP and accounting teams to jumpstart your projects.

Ninox Standout Features and Integrations:

Features I found valuable are that you can use Ninox on-prem, Ninox cloud, or get a dedicated server. You can access your data with its iPhone, iPad, Mac, and Android apps to ease your workflow further. It also provides features to easily create professional-looking forms and reports without any coding knowledge, customize the layout, fields, and colors to match your branding, and export them to PDF, CSV, or Excel formats for further analysis.

Integrations are available via Zapier, Make, and APIs.

Caspio is a low-code platform that allows businesses to create custom web applications and databases without extensive programming knowledge. Businesses that require a customizable and scalable solution that is easy to use and manage can find Caspio useful.

Why I picked Caspio: I included Caspio in this list because it has an intuitive, drag-and-drop interface and pre-built templates where users can easily build custom web forms, reports, and business applications. Users don’t need coding knowledge to create, publish, and manage online databases, and there are a variety of deployment options, including embedding apps within websites, sharing with others via URL, and integrating with external systems.

Caspio Standout Features and Integrations:

Features that I want to highlight here are that you can create responsive web apps with their application builder with point-and-click tools, use Caspio DataPages to create dynamic widgets, transfer data from various platforms like Box, Dropbox, Google Drive, and OneDrive, set fine-grained permissions down to individual tables, support multi-user access with password encryption and role-level privileges, and get support for a variety of file types like .txt, .csv, .xlsx, and .mdb.

Integrations are available natively for Salesforce, Microsoft 365 Excel, PayPal, Stripe, QuickBooks, HubSpot, Mailchimp, and Twilio, along with Zapier connection for other apps.

ScaleGrid is a DBaaS provider that lets you deploy your databases on public and private clouds and on-premises. ScaleGrid manages the infrastructure, which includes configuring, backing up, and securing the databases.

Why I picked ScaleGrid: I chose ScaleGrid because it lets you deploy and scale popular databases like Redis, MongoDB, MySQL, Greenplum, PostgreSQL, and SQL Server. You can even use your own cloud choosing from AWS and Azure. What is distinctive about ScaleGrid that I haven’t found in many options is that it provides SSH access to the underlying machine. With SSH access, users can directly interact with the server and perform actions outside the database's scope, such as installing additional software or tweaking server configurations.

ScaleGrid Standout Features and Integrations:

Features that I feel teams will find helpful are that you get a single console management even when you use multiple databases. It also provides fully customizable disk size, instance type, and RAM, and you can configure MySQL to perform repetitive tasks automatically and set schedules for backups.

Integrations are available natively for PagerDuty, Slack, Opsgenie, and Okta. APIs are available for integration.

MongoDB’s DBaaS runs on major cloud providers like AWS, Google Cloud Platform, and Azure. It’s a document-oriented database that stores data in JSON-like documents, which makes it easy to represent hierarchical relationships and complex structures.

Why I picked MongoDB: A compelling reason for me to select MongoDB for this list is that it is a NoSQL database that allows businesses to store and manage unstructured data (such as social media updates). It scales horizontally, which helps distribute data, and its cross-region replication ensures that data is replicated in multiple regions and is highly available even if one region experiences an outage.

MongoDB Standout Features and Integrations:

Features that I feel distinguish it from other options are elastic scalability, which lets you adjust resources allocated to your database on demand without any manual intervention. This allows you to handle sudden rises in data volume or traffic without worrying about capacity limits. It also offers multi-cloud clusters, automatic load balancing for read and write operations, and supports high availability and disaster recovery.

Integrations are natively available via connectors, including Apache Spark, Apache Kafka, Tableau, Postman, Vercel, Mongoose, Prisma, and JDBC. APIs are also available.

Azure SQL provides DBaaS solutions, which enable you to deploy, scale, and dynamically adjust your databases on the cloud without any need to manage the underlying infrastructure.

Why I picked Azure SQL: I picked Azure SQL because it’s a relational database. Relational databases store and manage data in tables, where each table represents a set of related data. These provide a flexible and scalable data storage option and are commonly used to manage data such as customer information, orders, and inventory. Businesses can use Azure’s Hyperscale capabilities that support 100TB of database size, perform quick backups and restores in case of infrastructure failures, and rapidly scale up to work through heavy workloads.

Azure SQL Standout Features and Integrations:

Features that impressed me during my evaluation are the concept of elastic pools that let you scale your business without any downtime, automatic tuning that automates the performance of queries, and Advanced Threat Protection that identifies unusual activities and sends you alerts to keep data safe.

Integrations are offered natively, including Azure DevOps, Azure Active Directory, Power BI, Azure Machine Learning, and Azure Data Factory.

As businesses grow, they need a scalable database management system to support their operations. SAP HANA Cloud is ideal for growing teams as it offers high-speed data processing, real-time analytics, and advanced machine learning capabilities.

Why I picked SAP HANA Cloud: I like SAP HANA Cloud’s DBaaS offering because it has many functionalities to support scaling teams. It supports multiple data models, federates data from your on-prem, cloud, or third-party sources, runs intelligent data applications and analytics on petabytes of data, and uses machine learning and predictive analytics techniques. It also has in-memory capabilities that allow faster data processing, query response, and auto scalability to adjust resources.

SAP HANA Cloud Standout Features and Integrations:

Features that stand out for me are a multi-tenancy option where growing teams can share resources and costs but get robust security, a workload analyzer tool to analyze database performance with thread samples, HANA studio to gather data related to performance and find out the root cause of issues, and comprehensive disaster recovery support.

Integrations are available pre-built for various SAP products and services, such as SAP Analytics Cloud, SAP Data Intelligence, and SAP Cloud Platform. It also has a SAP integration service to bring blockchain data to your database.

Oracle Autonomous Database is a self-driving database that uses machine learning algorithms to automate database management, thus reducing human error and eliminating downtime.

Why I picked Oracle Autonomous Database: I picked Oracle because it can automatically configure workloads, scale computing resources as required, patch your database if there’s any vulnerability, identify system failures, and perform failovers without data loss. It offers quick performance because it is preconfigured with indexes, data caching, and row formats.

Autonomous Database Standout Features and Integrations:

Features that I feel that Oracle Autonomous Database has that are important for businesses looking for automated workflows are advanced database technologies like Real Application Clusters that help in scale-out and online patching, Active Data Guard for disaster recovery, Database In-Memory for high performance, and graph analytics to support complex data relationships.

Integrations aren’t listed, but they have a list of products that Oracle is compatible with, which include Siebel CRM, Oracle Peoplesoft, dbt, Oracle SQL Developer, Cognos, CData Sync, and Dataiku.

Google Cloud SQL is a fully-managed, relational database service for MySQL, PostgreSQL, and SQL Server.

Why I picked Google Cloud SQL: The primary reason I believe that Google Cloud SQL is a good fit for remote teams is that it offers easy and secure collaboration with team members through role-based access control and private IP connectivity to VPC networks. It also has a user-friendly web UI and command line interface for managing databases accessible by technical and non-technical users.

Google Cloud SQL Standout Features and Integrations:

Features that I want to highlight here are that it provides automatic backups and point-in-time recovery and enables scaling up or down of database instances to accommodate changing team needs. It also supports both standard and custom machine types for greater flexibility in performance and cost and has built-in monitoring and logging to troubleshoot issues.

Integrations are native and include connections with App Engine, Compute Engine, Google Kubernetes Engine, and BigQuery.

Amazon DynamoDB is a fully-managed NoSQL database that enables you to create software applications, build metadata stores for media content, manage retail operations, and run gaming platforms.

Why I picked Amazon DynamoDB: Amazon DynamoDB's ability to read and write capacity modes makes it a good fit for enterprises. I like that you can choose their on-demand mode, where Amazon manages capacity for you, and you just pay for what you consume. This allows enterprises to scale their workloads according to changing traffic levels. However, you can choose provisioned mode, where you set a limit to read and write capacity if you have an estimate of the utilization.

Amazon DynamoDB Standout Features and Integrations:

Features that I find impressive are the ability to autoscale throughput, which means Amazon DynamoDB can handle a high volume of requests without slowing down. I also like that it offers native, server-side support for atomicity, consistency, isolation, and durability (ACID) transactions, which ensure data is consistent in a database.

Integrations are natively available for AWS Lambda, Amazon Redshift, Amazon S3, Amazon EMR, and Amazon Cognito.

Fauna is a serverless, JAMstack-oriented, globally distributed database that seeks to simplify building applications with a flexible data structure.

Why I picked Fauna: I added Fauna to this list because it offers global distribution that allows you to store your data closer to your users, reducing latency and improving performance. Plus, it shards your data automatically across multiple nodes ensuring high availability and fault tolerance. Fauna is API-based and provides native GraphQL support, making it easier for developers to query and manipulate data — even with complex relationships.

Fauna Standout Features and Integrations:

Features that I liked about Fauna are that you can query a variety of data structures, including documents, graphs, and relational data. It’s also atomicity, consistency, isolation, and distribution (ACID) compliant, so you can ensure data consistency and integrity when your databases are distributed. It offers real-time streaming capabilities, which makes it easy to build event-driven architectures and real-time applications.

Integrations are available as pre-built options, including Netlify, Vercel, Microsoft Azure, Auth0, Cloudflare, AWS, Google Cloud, Okta, Retool, and Appsmith.