CrateIO VS Amazon Aurora

Compare CrateIO VS Amazon Aurora and see what are their differences

monday.com

The most intuitive platform to manage projects and teamwork featured

Contents:

» Base Details
» Videos
» Reviews
» Alternatives

Amazon Aurora

MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.

Landing page //
2023-09-17

Landing page //
2023-03-17

CrateIO

Website: crate.io
Pricing URL: Official CrateIO Pricing
Release Date: 2013 January
Startup details
Country: United States
State: California
City: San Francisco
Founder(s): Bernd Dorn
Employees: 50 - 99

Edit details

Amazon Aurora

Website: aws.amazon.com
Pricing URL: -
Release Date: 2014 October

Edit details

CrateIO features and specs

Scalability
CrateIO offers horizontal scalability, allowing you to handle large volumes of data and high traffic by simply adding more nodes to the cluster. Its distributed architecture makes it suitable for scaling with growing data demands.
Ease of Integration
CrateIO is designed to integrate well with existing systems. It supports standard SQL queries, making it accessible for developers familiar with relational databases. Additionally, it provides RESTful APIs for easy integration with other applications.
Real-time Analytics
CrateIO is optimized for real-time analytics and data processing, making it ideal for applications that require immediate data insights and fast querying speeds.
Dynamic Schema
The dynamic schema feature of CrateIO allows for flexibility in handling changes in the data model. Users can easily add new fields to a table without downtime, catering to agile development and evolving data structures.

Possible disadvantages of CrateIO

Limited Advanced SQL Features
While CrateIO supports SQL, it may lack some advanced SQL features that are available in traditional relational database systems. This might be a limitation for applications that rely heavily on complex SQL queries and transactions.
Indexing Overheads
CrateIO's use of Elasticsearch for indexing can lead to performance overheads, especially in scenarios with frequent write operations that require constant index updates.
Complex Configuration
Setting up and configuring a CrateIO cluster can be complex, especially for organizations without prior experience with distributed systems, requiring a learning curve and potentially more time to set up correctly.
Community and Ecosystem
CrateIO's ecosystem and community are smaller compared to more established databases, which might limit the availability of ready-made solutions or community support for niche use cases.

Amazon Aurora features and specs

High Performance
Amazon Aurora is designed to provide up to five times the throughput of standard MySQL and three times the throughput of standard PostgreSQL databases.
Scalability
Aurora scales storage automatically, growing from 10GB up to 128TB with no downtime. This automatic scaling makes it ideal for applications with fluctuating workloads.
High Availability and Durability
Aurora automatically replicates six copies of data across three availability zones and continuously backs up data to Amazon S3, ensuring durability.
Security
Aurora offers multiple layers of security including network isolation using Amazon VPC, encryption at rest using keys that you create and control through AWS Key Management Service (KMS), and encryption of data in transit using SSL.
Fully Managed
Aurora is fully managed by AWS, which automates time-consuming administrative tasks such as hardware provisioning, database setup, patching, and backups.
Compatibility
Aurora is compatible with MySQL and PostgreSQL, making it easier to migrate existing applications to Aurora with minimal changes.

Possible disadvantages of Amazon Aurora

Cost
Aurora can be more expensive than traditional RDS instances, particularly for workloads that do not fully utilize its high performance and scalability features.
Complexity
The numerous features and configurations can make Aurora complex to manage and tune, especially for those who are not familiar with AWS services.
Vendor Lock-in
Adopting Aurora ties you into the AWS ecosystem, which can make it difficult to migrate to other cloud providers or on-premises systems.
Cold Start Latency
Aurora Serverless can experience latency during cold starts, which can be problematic for applications requiring instant scalability.
Limited to AWS Environment
Aurora is only available within the AWS environment, which can be limiting if your infrastructure spans multiple cloud providers.

Analysis of Amazon Aurora

Overall verdict

Amazon Aurora is generally regarded as an excellent database service for businesses that require robust performance and high availability. It strikes a balance between cost-effectiveness and advanced database features, making it suitable for a wide range of applications.

Why this product is good

Amazon Aurora is considered a good choice for many applications due to its high performance, scalability, and compatibility with popular database systems like MySQL and PostgreSQL. It offers features like automated backups, quick failover, and replication capabilities. Aurora is designed to be fault-tolerant and highly available, providing a fully managed solution that relieves users from the operational burden associated with on-premise database management.

Recommended for

Amazon Aurora is recommended for organizations that need reliable, scalable, and high-performance databases. It is well-suited for web and mobile applications, e-commerce platforms, real-time analytics, and other use cases requiring high availability and fault tolerance. It's ideal for businesses looking to modernize their database infrastructure and take advantage of cloud-native capabilities.

CrateIO videos

No CrateIO videos yet. You could help us improve this page by suggesting one.

Add video

Amazon Aurora videos

+ Add

Introduction to Amazon Aurora - Relational Database Built for the Cloud - AWS

Category Popularity

0-100% (relative to CrateIO and Amazon Aurora)

CrateIO

Amazon Aurora

Databases

12 12%

Databases

88% 88

Relational Databases

11 11%

Relational Databases

89% 89

NoSQL Databases

20 20%

NoSQL Databases

80% 80

SQL Database

100 100%

SQL Database

0% 0

User comments

Share your experience with using CrateIO and Amazon Aurora. For example, how are they different and which one is better?

Social recommendations and mentions

Based on our record, Amazon Aurora should be more popular than CrateIO. It has been mentiond 23 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

CrateIO mentions (12)

A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
CrateDB - Distributed Open Source SQL database for real-time analytics. Free Tier CRFREE: One-node with 2 CPUs, 2 GiB of memory, 8 GiB of storage. One cluster per organization, no payment method needed. - Source: dev.to / over 1 year ago
varpro 0.6: Fast and Simple Nonlinear Fitting
Not necessarily argmin{}, but it appears as one of top download in crate.io. Again, that's just a suggestion. VarPar seems like a subset of bigger "optimization", but I might be wrong. I am not affiliated to argmin{} at all. I am still learning argmin{} and have not even get my first optimization to run properly. Do I want to learn new workflow again ... hmm.. A search in crate.io for "optimization" yield tons... Source: about 2 years ago
A good, fast hash for nucleotides triplet converted to 0, 1, 3, 2 using `3 & (nuc << 1)`
I really, really don't understand what the big deal with Rust is. I like to call Rust "LLVM's Python". It's a language for people who don't know how to debug segfaults lol. This is coming from me a person who loves Rust, despite all its faults, I believe if used as a low-level language, it can flourish to hell and back. But if you are going to use it as a webframework and load dozens of crate.io libraries on it,... Source: about 2 years ago
Unable to compile rand_core
There's 3 more errors that amount to the same thing. So I run cargo update. Same result. Explicitly tried to update cfg-if then rand_core with --verbose and --aggressive. No output beyond "updating crate.io index." Checked in browser for updates. cfg-if had no new versions since 2018. Then I tried using cargo clean first. Same result. Source: about 2 years ago
Stop Comparing Rust to Old C++
However, I do say that my general points still holds: most user's composing their types will get the right defaults and if they need anything more exotic, the users and domain specialist can very easy coordinate via crate.io . Source: over 2 years ago

Amazon Aurora mentions (23)

Building a RAG System for Video Content Search and Analysis
Using Amazon Bedrock to invoke Amazon Titan Foundation Models for generating multimodal embeddings, Amazon Transcribe for converting speech to text, and Amazon Aurora postgreSQL for vector storage and similarity search, you can build an application that understands both visual and audio content, enabling natural language queries to find specific moments in videos. - Source: dev.to / about 2 months ago
Everyone Uses Postgres… But Why?
Cloud deployment: PostgreSQL can be deployed in the cloud with AWS RDS, Amazon Aurora, Azure Database for PostgreSQL, or Cloud SQL for PostgreSQL. - Source: dev.to / 7 months ago
Announcing the public beta for dedicated clusters
Today, our Postgres databases are Amazon Aurora instances. You can trust that your database will have the scalability, reliability and security that AWS is known for. With dedicated clusters you can configure both the Postgres engine version, cluster class and number of replicas for failover and query distribution. - Source: dev.to / 10 months ago
Vector database is not a separate database category
As far as the big players are concerned, Google offers AlloyDB (https://cloud.google.com/alloydb) while Amazon offers Aurora (https://aws.amazon.com/rds/aurora/). - Source: Hacker News / over 1 year ago
Building realtime experiences with Amazon Aurora
Aurora is a managed database service from Amazon compatible with MySQL and PostgreSQL. It allows for the use of existing MySQL code, tools, and applications and can offer increased performance for certain workloads compared to MySQL and PostgreSQL. - Source: dev.to / almost 2 years ago