The EDB Postgres Advanced Server is an advanced deployment of the PostgreSQL relational database with greater features and Oracle compatibility, from EnterpriseDB headquartered in Bedford, Massachusetts.
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MongoDB
Score 8.9 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
million reads
Neo4j
Score 8.8 out of 10
N/A
Neo4j is an open source embeddable graph database developed by Neo Technologies based in San Mateo, California with an office in Sweden.
$65
per month
Pricing
EDB Postgres Advanced Server
MongoDB
Neo4j
Editions & Modules
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Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Aura Professional
$65
per month
Community Edition
Free
Enterprise Edition
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Aura Free
Free
Aura Enterprise
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Offerings
Pricing Offerings
EDB Postgres Advanced Server
MongoDB
Neo4j
Free Trial
No
Yes
Yes
Free/Freemium Version
No
Yes
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
EDB Postgres Advanced Server
MongoDB
Neo4j
Considered Multiple Products
EDB Postgres Advanced Server
No answer on this topic
MongoDB
Verified User
Program Manager
Chose MongoDB
There are use cases for both relational and non-relational databases. MongoDB is simply a different method of storing data, but I find it to be faster and more intuitive than relational models.
Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join …
Neo4j is ahead of any of the leading competitors I know. The only one which comes close, in my opinion, is the "Titan-Distributed Graph Database" which is completely open source and free to use. Titan works on top of Apache Cassandra so it has some huge learning curves to do, …
It's great if you are using or wish to use PostgreSQL and need the added performance optimization, security features and developer and DBA tools. If you need compatibility with Oracle it's a must-have. There are many developer features that greatly assist dev teams in integrating and implementing complex middleware. It's great for optimizing complex database queries as well as for scaling. I would recommend Postgres Plus Advanced Server for any software development team that is hitting the limit of what PostgreSQL is capable of and wants to improve performance, security, and gain extra developer tools.
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.
Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using Tableau, for example.
PPAS Oracle compatibility, especially the PL/SQL syntax, has made migrating database-tier code very simple. Most Oracle packages do not need to be changed at all and those that do are generally for simple reasons like a reserved word in PPAS that is allowed in Oracle.
PPAS xDB, the multi-master replication tool, is simple and - most important - does not break with network or other interruptions. We have been able to configure and forget, which our customers could never do with other multi-master tools.
Most people had no idea that PPAS and PostgreSQL have full CRUD support for JSON. They think you need a specialized product and/or that JSON is read-only. Every organization that I have worked with is evaluating adding JSON to their relational model.
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.
Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
Native support for REST API, that makes interacting with Neo4J intuitive and easy.
Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
Nice UI and interface for executing the Query and visualizing the response.
UI access controlled by User credentials allows for neat access controls.
Awesome free community edition for small-scale projects.
Documentation is excellent but spread out across many resources and can take a while to wade through—would benefit from having more intro level, getting started guides for various languages.
Ruby support is excellent but more Ruby examples and beginner-level documentation would be nice.
It is sometimes hard to find a community of users on StackOverflow so a larger community, and a dedicated forum with active members to answer questions and work through issues would be nice.
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.
One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.
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.
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.
Learning cypher was super easy coming from a SQL background. Furthermore, the docs Neo4j provides on their website make it really easy to pull up a reference, guide or a quick example. The mac app they provide is also really well designed with good visualisation tools, with the ability to easily use colour, line thickness etc to help navigate your data.
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.
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.
PPAS proved better for our customer's data-centric apps than Oracle in all but a few edge cases (encryption at rest and multi-TB database-tier backups) because it is simpler to install/maintain, runs nearly all Oracle-syntax SQL as well as ANSI SQL. PPAS has much more JSON capabilities (full CRUD vs. read-only in Oracle), simpler geospatial, simpler / more stable replication and datatypes that match developer expectations, such as BOOLEAN and ENUMs.
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.
Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive. MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to MongoDB yet, whereas Neo4J is ACID complaint with all its operations.
Postgres Plus Advanced Server is quite complex and may take longer to implement certain things than simply using PostgreSQL depending on developer familiarity with the platform.
Getting up to speed can be daunting so again, there is an upfront cost in time spent learning the platform, besides the potential for extra time spent on a feature-by-feature basis.
The cost of Postgres Plus Advanced Server should be weighed against simply using PostgreSQL to decide which is the best solution for your business needs.
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