Astra DB from DataStax is a vector database for developers that need to get accurate Generative AI applications into production, fast.
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MongoDB
Score 8.5 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0
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Astra DB
MongoDB
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Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
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Astra DB
MongoDB
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
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Astra DB
MongoDB
Considered Both Products
Astra DB
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Chose Astra DB
We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and …
We selected Astra for reducing complexity of our operations, local support, scalability, reliability, and business continuity/contingency planning reasons. We're a small team so prefer a database-as-a-solution model.
Astra DB allowed us running a database without going deep into the configuration hell. It scales with our usage and therefore, there was no need to learn the sepcialities of a vector database.
For the workloads we use Astra DB for it was a better choice than the other databases. It worked out to be more scalable and cost affective than the traditional relational databases. Also performant and without the downsides of size limits compared to other services.
I never tried Pinecone with a production workload, but I can say that the enterprise support and care of DataStax is game changer. They really put effort in creating with you a valid and effective solution for your business.
Astra DB is at par with each one of them as it's scalability and availability is unmatched. The best thing about Astra DB is it's managed service takes care of database operations, freeing up development teams to work on application features. With its scalable architecture and …
Astra DB is a managed database service based on Apache Cassandra that is mostly used for NoSQL data storage and administration, whereas Azure is a full cloud computing platform provided by Microsoft that includes infrastructure, platform, and software services. Astra DB is …
Astra DB, which is built on Apache Cassandra, is well-known for its smooth horizontal scalability, making it an ideal solution for applications with quickly rising data and traffic. Although MongoDB Atlas provides high availability, Astra DB's multi-region capability can …
Since I was familiar with CQL, choosing Astra DB was the only smart choice for me. It is equally capable as all the other cloud-based fully managed database services currently out in the market. It provides very good documentation also for people who are new to it, making it …
Astra DB supports Cassandra which is very important and of key notice. We work on Cassandra , thus we need Astra DB. Astra DB has high availability and scalability. The customer service provided by Astra DB is really helpful and the response is always available. Astra DB has …
Astra DB supports apache cassandra which in itself is a plus point. It's primary database model has a wide column store. Deployment of Astra Db takes minutes in AWS, Google Cloud, Azure. Also it is schema free. It also has advanced replication for edge computing. In other …
The tools astra db provides are much more effective and efficient, especially the integration allowed within astra db. One can customize the choice of tools as per their requirements.
Astra DB has a better database system than Mongo DB and that why me and my team prefers using Astra DB over all the database tools available. The Apache Cassandra database is what attracts the user to Astra DB rather than other databases. Wide Column storing database is what we …
Astra in the general case ends up coming in cheaper than it costs to run your own VMs on a VPS to self-host either cassandra or scylla. How they do that, I don't know, but I'm glad they do!
Some advantages of Cassandra by itself over the other solutions is being masterless and column oriented. About Astra DB, for us the decision-making factor was having a serverless solution and with the latest Cassandra version and features, additionally it provides a rich set …
I have previously used and evaluated MongoDB and MySQL for various projects before choosing AstraDB for my chatbot application. While MongoDB and MySQL are both powerful and popular database solutions, AstraDB stood out for specific reasons in the context of my project.MongoDB, …
Graph, search, analytics, administration, developer tooling, and monitoring are all incorporated into a single platform by Astra DB. Mongo Db is a self-managed infrastructure. Astra DB has Wide column store and Mongo DB has Document store. The best thing is that Astra DB …
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for …
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your …
Both Couchbase and MongoDB are document-oriented NoSQL databases, so they have very similar features. While they do have some fundamental differences in terms of how they scale, shard, etc. the one key reason why we went with MongoDB is its availability and support from the …
The flexible structure underlying MongoDB's construction is not found in other competitors; the ability to easily change the structure without affecting other stored documents. It is very ideal for projects that you cannot predict that the structure will change this way. Of …
Implementing new features for application becomes simpler with MongoDB since you don't need to run database migration scripts just to for example add new fields to database only to store some extra data. This is especially good for the deployment phase. Only new version of …
MongoDB is a robust and scalable db which offers a lot of cool features out of the box. Being open sourced and backed by a great community with developer tools like mongo compass , it was a no-brainer to go for it. It has connectors in almost all programming languages and is a …
I would say Cassandra is better than MongoDB since it has the backing of Facebook to it. Its inherent properties like versioning put it into the other category of columnar databases, but it's one of the NoSQL databases which you should definitely consider for your organization …
This tool is only capable of reading real-time data very smoothly. The transition was also pretty easy and quick. Syntax is also very easy and comfortable to learn and use.
The main reason for selecting is that it works very fast under the Intellijet module environment and we …
In our early development days we weighed NoSQL databases like MongoDB with RDBMS solutions like MySQL. We were more familiar with MySQL from past experience but also were wary of painful data migrations that slowed down development iterations and increased the risk of outages …
Snowflake and Redshift are much more mature and have been around longer. MongoDB is definitely much less expensive and if you are in a startup, this is an almost for-sure option. Redshift can be slow and Mongo is much faster. However, losing the relational database aspect could …
It's very fast and easiest to use. Many companies are using this nowadays. It's helped to complete many software products very quickly so the year income has increased compared with last years. Many programmers are now leaning this tool as back end developers so that we changed …
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with firebase. If you …
It does not belong to certain cloud platforms. MongoDB is an independent program that works with any cloud platform including Amazon Web Services and the Google Cloud Platform. For companies who want to maintain a cloud agnostic structure, MongoDB is a great choice for NoSQL …
MongoDB and Cassandra are both database system from the NoSQL family. MongoDB can be used in lots of use cases while Cassandra has a specific usage. There are some features that MongoDB provides efficiently while Cassandra doesn't and vice-versa. Like, you can update the data …
We tend to choose MongoDB when we're faced with a particular situation: we know that we need a NoSQL database in general, and want an open-source implementation that allows us to prevent against platform lock-in. Amazon's new DocumentDB product even allows us to choose to use …
We use Astra DB to improve our management systems. Storing data has become hassle-free and quite simple. When launching a Cassandra-based cloud application, Astra DB is exactly what you need. In addition to the standard training programs and videos, the extended support and training require significant additional effort to activate and cover which I feel is a bit more tedious task.
MongoDB [is] great at storing JSON data grouped into "collections". In this format, you can store any JSON documents and conveniently categorize them by collections. The JSON document contained in MongoDB is called binary JSON or BSON and, like any other document in this format, is unstructured. Therefore, unlike traditional DBMS, any kind of data can be stored in collections, and this flexibility is combined with the horizontal scalability of the database. It should be noted that MongoDB does not have links between documents and “collections” (this is partially compensated by the Database Reference - links in the DBMS, but this does not completely solve the problem). As a result, a situation arises in which there is a certain set of data that is not related to other information in the database, and there is no way to combine data from different documents. In SQL systems, this would be an elementary task.
We need to be able to process a lot of data (our biggest clients process hundreds of milions of transactions every month). However, it is not only the amount of data, it is also an unpredictable patterns with spikes occuring at different points of time - something athat Astra is great at.
Our processing needs to be extremaly fast. Some of our clients use our enrichment in a synchronous way, meaning that any delay in processing is holding up the whole transaction lifecycle and can have a major impact on the client. Astra is very fast.
A close collaboration with GCP makes our life very easy. All of our technology sits in Google Cloud, so having Astra in there makes it a no-brainer solution for us.
Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
Fast performance.
It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
Query syntax is pretty simple to grasp and utilize.
Aggregate functions are powerful.
Scaling options.
Documentation is quite good and versioned for each release.
Astra DB might be difficult to understand for people who are unfamiliar with Apache Cassandra. Improving the initial experience for newcomers, as well as offering better documentation and lessons, might be advantageous.
The Astra DB ecosystem may be enhanced by expanding the ecosystem of plugins, integrations, and community-contributed solutions.
MongoDB is one of the most famous non-relational databases in the world, there are famous active projects that use this database. I think that the same company that develops the database gives you the online induction totally free is something that really is very positive. Accounts with a first-class support to be able to relate the correct implementation of the database, in addition to teaching you the best practices to optimize your projects, I believe that with this decision it is more than obvious which is the best decision at the time of seeing with which database to work.
It is one of the reasons why we prefer it to store documents in a JSON-style format, to access the desired document very quickly regardless of its size, to be readable by human eyes, and to be easily scalable and manageable.
Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.
I have reached multiple times to the MongoDB community for the help and they have provided each and easy solution for every problem. Over the internet and on stack overflow many people responds over the challenges. Now this tool is very much used in every company and projects so internally many people are there to give a support.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and strong reliability, allowing Maester’s development team to prioritize high-value, customer-facing features
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for quick retrieval later. This is something we can't easily do with MySQL. On this smaller database, MongoDB also lets us retrieve data more quickly with its fast and efficient querying.
We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.
Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.
Database growth planning is less of a concern with Astra, as it scales automatically.
Currently, they lack fine-grained security at the table level. I suspect that will change over time.
If your load has peaks and valleys; Astra enables only paying for Reads/Writes; thus you do not need to pay for large servers to support peaks in load.
We can make more open and flexible systems due to its easy adaptation to new evolutions in web applications.
In the latest versions it offers support for different transactions and we could carry out real tests related to the concurrency of the application.
MongoDB allows you to have distributed clusters, which improves the speed of the queries by reducing the latency that exists between the database cluster and the service that executes the query.