Data is everywhere around us and we interact with it regularly. Whether you’re checking out the latest model of a smartphone or buying groceries online, you are interacting with data in one way or the other. We have been dealing with data for ages, what has changed now is the scale of data produced and the speed at which it is accessed.
Thanks to digital technologies like cloud, IoT (Internet of things), AI (Artificial Intelligence), machine learning, and more, companies are producing data at an exponential rate. This amount of data collected around the globe is too hefty to process.
According to a report, “People are generating 2.5 quintillion bytes of data each day.”
Here, traditional relational databases like SQL might not offer the required scalability and performance to process large amounts of data. Though relational databases are still relevant, alternative databases like NoSQL come with their own sets of advantages.
This article will help you understand:
- What is NoSQL database?
- What are the advantages of NoSQL database?
- A detailed comparison between top NoSQL database solutions provided by Alibaba Cloud, AWS, Google Cloud, IBM, and Microsoft
- Tabular Comparison – DynamoDB Vs Bigtable Vs Cloudant Vs Tablestore Vs CosmosDB
- Picking the right NoSQL database service – tips
What is NoSQL database?
NoSQL stands for ‘not only SQL’. Big infrastructure providers like Google, Amazon, and Facebook recognized the scalability issue of SQL databases and hence introduced their alternative solutions like Bigtable, DynamoDB, and Cassandra, respectively to meet the changing demands.
NoSQL is an approach to database design. It can accommodate a wide variety of data models. Some of these include key-value, columnar, document, and graph formats. It offers improved scalability, performance, reliability, and consistency as compared to schema-based traditional relational databases.
The NoSQL databases are purpose-built to work with large sets of distributed data. They mostly refer to the databases built in the early 2000s for large-scale clustering of data produced by cloud and web applications.
The need for performance and scalability in cloud-based web applications outweighs the rigid data consistency that traditional relational database management systems provide.
NoSQL database is a form of unstructured storage. They do not have any fixed table structure – one important trait that differentiates them with the common relational databases.
- NoSQL databases have a flexible schema. There can be different rows having different attributes or structure.
- They work on a BASE model – Basically Available, Soft state, Eventual consistency.
- In NoSQL, queries may not always see the latest data. Thus, consistency is guaranteed after some period.
The advantages of NoSQL databases
- NoSQL databases have a simpler structure without a schema and are flexible.
- They are based on key-value points. This means that records are stored and retrieved using a key that is unique to every set of record.
- NoSQL database can also have column store, key-value graph, document store, object store and other popular data store modes. Thus, they are multi-purpose as well.
- Open-source NoSQL databases don’t require any expensive licensing fees.
- They are easily scalable whether you are using an open-source or a proprietary solution. This is because the NoSQL databases can scale horizontally to distribute the load on all nodes. In SQL, this is done by replacing the main host with a higher capacity one, i.e. via vertical scaling.
Now when you know what NoSQL is and what are its advantages, it is time to look at some of the top NoSQL database solutions offered by leading service providers like AWS, Google Cloud, IBM, Alibaba Cloud, and Microsoft. We will also be taking a look at a NoSQL database comparison table for understanding the key differences.
Comparison between NoSQL database solutions
1. Alibaba Cloud Tablestore
Tablestore is a fully managed NoSQL cloud database service offered by Alibaba Cloud. It can store a large amount of structured and semi-structured data using a variety of data models. Users can use Tablestore database to query and analyse data. Users can also migrate heterogeneous data to this database without any interruptions. With elastic resources and pay-as-you-go billing, it is an efficient and low-cost database management system. It offers high-consistency and service availability with globally spread data centres. Furthermore, distributed architecture and single table auto-scaling makes it highly elastic.
- It is a fully managed database service. Users can simply focus on business research and development activities instead of worrying about hardware and software presetting, faults, configurations, security, etc.
- With in-built shards and load balancing, Tablestore can automatically adjust the size of partitions, allowing users to store more data.
- It creates multiple backups of data and stores them in different server racks.
- It also offers consistency across three backups. The application can quickly read the data.
Source: Alibaba Cloud
2. Amazon DynamoDB
Amazon DynamoDB is a fast and flexible NoSQL database service that can deliver single-digit millisecond performance at any scale. It is a key-value and document database that is multi-region, fully managed, and durable.
The multi-master database is backed with in-built security, backup, restore, and in-memory caching for internet-scale applications.
- DynamoDB is built to support the world’s largest-scale applications.
- Users can build applications with unlimited throughput and storage.
- The data stored in the database is replicated across multiple AWS regions. This allows local access to data for globally distributed applications.
- Another great advantage of DynamoDB is that it is serverless. Users have no servers to manage or provision.
- The database is designed to scale automatically up and down as per the system and capacity requirement.
- It also supports ACID (Atomicity, Consistency, Isolation, and Durability) transactions – making it an enterprise-ready database.
Reference Architecture of a Weather Application, Source: Amazon Web Services
3. Azure Cosmos DB
Azure CosmosDB is a NoSQL database service by Microsoft that is globally distributed and multi-model. It allows users elastically and independently scales workloads with a click of a button.
Users can also take advantage of fast, single-digit-millisecond data access with the help of APIs like Cassandra, SQL, MongoDB, Gremlin or Tables. It provides comprehensive service level agreements (SLAs) for latency, throughput, availability, and consistency guarantees.
- With globally spread Azure regions, users can build highly responsive and highly available applications worldwide.
- It provides 99.999% availability for both write and read actions. It is deeply integrated with Azure Infrastructure and Transparent Multi-Master replication.
- It offers unprecedented elastic scalability through transparent horizontal partitioning and multi-master replication.
- Users do not need to deal with index or schema management as the database engine is fully-schema-agnostic.
Source: Microsoft
4. Google Cloud Bigtable
Cloud Bigtable is the fully managed and scalable NoSQL service by Google Cloud. It is best suited for large analytical and operational workloads. It allows users to store terabytes or even petabytes of data. It is ideal for storing large amounts of single-keyed data with very low latency. Cloud Bigtable stores data in scalable tables. These tables are composed of rows and columns. Each of the rows describes a single entity and are indexed by a single row key.
Data stored inside the Cloud Bigtable database is completely secure. The access to the data is controlled by Google Cloud project and the Identity and Access Management (IAM) roles. It also allows users to save a copy of schemas and data as backups.
- Cloud Bigtable database is designed to scale in direct proportion to the number of machines in a cluster.
- It can handle upgrades and restart automatically.
- Users can also increase the size of a Cloud Bigtable cluster for a few hours to manage any large loads.
It is ideal for time-series data, marketing data, financial data, internet of things’ data, and graph data.
IoT use case reference architecture, Source: Google Cloud
5. IBM Cloudant
IBM Cloudant is a fully managed database service designed for hybrid multi-cloud applications. It is built on open-source Apache CouchDB and has a fully compatible API that allows data syncing to any cloud or the edge.
It is a distributed database service that can handle heavy workloads of large, fast-growing web and mobile apps. It is available as an SLA-backed and fully managed IBM Cloud service. Users can also download the service for on-premises installation.
- It allows users to instantly deploy an instance, create a database, and independently scale.
- It is ISO 27001, SOC 2 Type 2 compliant and HIPAA ready.
- With 55+ data centres across the world and globally spread IBM Cloud regions, users can seamlessly distribute data across zones, regions, and cloud providers.
- The service is compatible with Apache CouchDB, enabling users to access a wide variety of language libraries and rapidly build new applications. Thus, the service boasts of zero vendor lock-in.
AI use case, Source: IBM
Tabular Comparison
NoSQL Database Comparison: DynamoDB Vs Bigtable Vs Cloudant Vs Tablestore Vs Azure CosmosDB
| Comparison Points | DynamoDB | Cloud BigTable | Cloudant | Tablestore | Azure CosmosDB |
| Developed By | Amazon Web Services (AWS) | IBM | Alibaba Cloud | Microsoft | |
| Primary Database Model |
|
Wide Column store | Document Store | Wide Column Store |
|
| Initial Release | 2012 | 2015 | 2010 | 2016 | 2017 |
| License
|
Commercial | Commercial | Commercial | Commercial | Commercial |
| Cloud-based | Yes | Yes | Yes | Yes | Yes |
| Data Schema | Schema-free | Schema-free | Schema-free | Schema-free | Schema-free |
| Server OS | Hosted | Hosted | Hosted | Hosted | Hosted |
| Supported Programming Languages* |
|
|
|
|
|
| Consistency |
|
|
Eventual Consistency | Immediate Consistency |
|
| Durability | Yes | Yes | Yes | Yes | Yes |
| Partitioning Methods | Sharding | Sharding | Sharding | Sharding | Sharding |
| Use Cases* |
|
|
|
|
|
| Supported Data Types* |
|
Treats all data as raw byte strings for most purposes | NA |
|
NA |
| Latency | Microsecond latency with DynamoDB Accelerator (DAX) | Consistent sub-10ms latency | NA | Low latency | Read latency for all consistency levels is guaranteed to be less than 10 milliseconds at the 99th percentile |
| Replication | Automated Global Replication | Yes | NA | NA | Transparent multi-master replication |
| Triggers | Yes | No | Yes | No | JavaScript |
| Support for ACID transactions | Yes | Atomic single-row operations | No | Atomic single-row operations | Yes |
| Data Encryption | Yes | Yes (data encrypted at rest) | Yes (Data encrypted at rest) | NA | Yes (Data encrypted at rest) |
| Backup and Restore | On-demand backup and restore | Available | CouchBackup for snapshot backup and restore | Custom backup and restoration | Automatic and Online Backups |
| MapReduce | No | Yes | Yes | No | Yes (with the help of Hadoop Integration) |
Points marked asterisk (*) define an inclusive list in the above NoSQL Database Comparison Table
Suggested Reading: Relational Database Comparison – Alibaba, Amazon, Google, IBM and Microsoft
Picking the right NoSQL database service – tips
NoSQL database services include a wide and comprehensive set of feature-rich solutions to help you build better applications. However, you should not pick a database just because it offers a lot of features. You need to decide what your application and business needs are. Also, you need to consider factors like vendor-lock in to avoid being stuck with a single service provider.
While all the major NoSQL databases we discussed are popular and enterprise-ready, here are a few things you might want to consider when picking a NoSQL service:
- Define your database goals: Whether you want to store data as a record; build interactive applications requiring real-time data processing; store data for a backend customer application, etc.
- Consider the security of data: When you trust a service provider with your data, you must ensure that your data is not compromised and is safe and readily available when required.
- Consider latency: Latency defines the time taken for a web application to respond to a user’s query. For customer-facing applications, you should consider a database that offers the lowest latency.
- Consider the hosting choice: You can either go for a self-hosted or a managed database service. Again, it depends on your application requirement. For complex and mission-critical applications, managed services come handy.
We hope our NoSQL Database comparison will help you make the right choice.
Feel free to share your queries and feedback through the comment section below.
Disclaimer: The information contained in this article is for general information purpose only. Price, product and feature information are subject to change. This information has been sourced from the websites and relevant resources available in the public domain of the named vendors on 4th September 2020. DHN makes best endeavors to ensure that the information is accurate and up to date, however, it does not warrant or guarantee that anything written here is 100% accurate, timely, or relevant to the website visitors.
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