The Aerospike Real-time Data Platform aims to enable organizations to act instantly across billions of transactions while reducing server footprint up to 80%. The vendor states Aerospike multi-cloud platform powers real-time applications with predictable sub-millisecond performance up to petabyte scale with five-nines uptime with globally distributed, consistent data. Aerospike boasts customers such as Airtel, Experian, European Central Bank, Nielsen, PayPal, Snap, Verizon Media and Wayfair.
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CouchDB
Score 6.0 out of 10
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Apache CouchDB is an HTTP + JSON document database with Map Reduce views and bi-directional replication. The Couch Replication Protocol is implemented in a variety of projects and products that span computing environments from globally distributed server-clusters, over mobile phones to web browsers.
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MongoDB
Score 8.7 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.
$0.10
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Pricing
Aerospike
Apache CouchDB
MongoDB
Editions & Modules
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Shared
$0
per month
Serverless
$0.10million reads
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Dedicated
$57
per month
Offerings
Pricing Offerings
Aerospike
CouchDB
MongoDB
Free Trial
No
No
Yes
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No 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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Community Pulse
Aerospike
Apache CouchDB
MongoDB
Considered Multiple Products
Aerospike
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Chose Aerospike
Aerospike is much more performant than MongoDB, however there is much greater community adoption and support for mongo
Compared to the above for K/V lookups and writes, it is faster. However, less than 1 MB, i'd use Redis, if you're willing to write package for HA in Redis. However HA between Redis and aerospike, aerospike is top notch. K/V lookups were 20-30% faster than Redis, 50% faster …
I have briefly used MongoDB in other products, and it proved that it had better integration capabilities with Ruby on Rails and node.js software platforms, more than CouchDB. But I never had the chance to actually replace CouchDB with MongoDB in the current product to see what …
We looked at MongoDB and Firebase. MongoDB gives us the best working db engine with a very intuitive design. However, it does not work as well offline. Firebase was extremely hard to create searching and indexing. Using a third-party to search didn't work for us or at least it …
MongoDB and CouchDB are both document stores, but their concurrency models and ability to scale are very different. MongoDB cannot replicate / shard over unreliable links and network partitions have been the cause of data loss in the past. MongoDB has an easier query language …
Compared to MongoDB, CouchDB's Map-Reduce paradigm poses a steeper learning curve for SQL users. However, CouchDB's master-master replication is an advantage of implementing a load-balanced solution. Even though, currently, CouchDB has strong community support, as an open …
It has been 5+ years since we chose CouchDB. We looked an MongoDB, Cassandra, and probably some others. At the end of the day, the performance, power potential, and simplicity of CouchDB made it a simple choice for our needs. No one should use just because we did. As I said …
MongoDB is probably the most famous NoSQL database of the moment. it has become one of the most promising startups. Some companies that currently use MongoDB are Foursquare or eBay. This type of database is designed to perform queries and aggregations on large amounts of data. …
MongoDB was the most full-featured NoSQL database we evaluated - that offered atomic transactions at a document level, built-in HA & DR, open source, robust queries, and enterprise level support.
Other platforms had specific parts of what we were looking for - MongoDB had it all.
MySQL is a great for querying related data, but it's unable to store structured data and has a fixed schema. Also SQL can be non-intuitive. DynamoDB, CouchDB and Redis all make querying the data quite difficult and lack important features. The problem CouchDB tries to solve is …
MongoDB provides better performance on a big database. If you prefer to define indexes rather than a map/reduce function, MongoDB is good for you. It's quick to start it up and very easy to learn, basically no entry barrier. MongoDB's community is very welcoming.
We were developing an advertisement time auction application, where we had to store the client's personal details, advertisement-related details, location, and many other details. Moreover, we required a promotion, cookies, and a few more details from the front end. All this information is heavy in terms of size and cannot be lost if the server crash. So, we required an extremely fast disk database with high scalability and low throughput.
Great for REST API development, if you want a small, fast server that will send and receive JSON structures, CouchDB is hard to beat. Not great for enterprise-level relational database querying (no kidding). While by definition, document-oriented databases are not relational, porting or migrating from relational, and using CouchDB as a backend is probably not a wise move as it's reliable, but It may not always be highly available.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
It can replicate and sync with web browsers via PouchDB. This lets you keep a synced copy of your database on the client-side, which offers much faster data access than continuous HTTP requests would allow, and enables offline usage.
Simple Map/Reduce support. The M/R system lets you process terabytes of documents in parallel, save the results, and only need to reprocess documents that have changed on subsequent updates. While not as powerful as Hadoop, it is an easy to use query system that's hard to screw up.
Sharding and Clustering support. As of CouchDB 2.0, it supports clustering and sharding of documents between instances without needing a load balancer to determine where requests should go.
Master to Master replication lets you clone, continuously backup, and listen for changes through the replication protocol, even over unreliable WAN links.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
If money isn't an issue, and you're not on the cloud, then I'd go with Aerospike. If you're the cloud ie, aws or azure, then i'd stick with dynamoDB or Cosmos then. Aerospike is definitely not something you want to put into the cloud. It doesn't work well w/ cross regions. If cross DC, you'll have to write some stuff for data integrity checks.
Because our current solution S3 is working great and CouchDB was a nightmare. The worst is that at first, it seemed fine until we filled it with tons of data and then started to create views and actually delete.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
Couchdb is very simple to use and the features are also reduced but well implemented. In order to use it the way its designed, the ui is adequate and easy. Of course, there are some other task that can't be performed through the admin ui but the minimalistic design allows you to use external libraries to develop custom scripts
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
it support is minimal also hw requirements. Also for development, we can have databases replicated everywhere and the replication is automagical. once you set up the security and the rules for replication, you are ready to go. The absence of a model let you build your app the way you want it
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 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 data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB