Likelihood to Recommend If you are storing META data then MarkLogic is super useful as it retrieves everything so fast, while storing the whole data shows performance issues some times. If you have legacy systems then migrating from it would really require sweat and blood, on the other hand if you are in systems like Node.js you can simply integrate two systems easily. If you don't know how in the end your your data schema will look like then it's better to make a prototype using MarkLogic.
Read full review If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)
Read full review Pros Search was really advanced. Hard to set up and had limitations about semantical meanings between xml nodes, but provided very good search abilities. The organization of documents across collections and metadata was particularly useful. The REST abilities were very advanced and worked with XQuery well. Read full review [Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results. [Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases [Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store. [Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance. Read full review Cons MarkLogic still has a long way to go in fostering the developer community. Many developers are gravitating to the simple integrations and do not delve into the deeper capabilities. They have made tremendous strides in recent months and I am sure this will improve over time. Many of the best features are left on the floor by enterprises who end up implementing MarkLogic as a data store. MarkLogic needs to help customers find ways to better leverage their investment and be more creative in how they use the product. Licensing costs become a major hurdle for adoption. The pricing model has improved for basic implementations, but the costs seem very prohibitive for some verticals and for some of the most advanced features. Read full review We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch. Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types. Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables. Read full review Likelihood to Renew MarkLogic is expensive but solid. While we use open source for almost everything else, the backend database is too critically important. At this point, re-tooling for a different back end would take too much time to be a viable option.
Read full review Usability Very little about it can be done better or with greater ease. Even things that seem difficult aren't really that bad. There's multiple ways to accomplish any admin task. MarkLogic requires a fraction of administrative effort that you see with enterprise RDBMS like Oracle. MarkLogic is continually improving the tools to simplify cluster configuration and maintenance.
Read full review Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
Read full review Support Rating There's always room for improvement. Some problems get solved faster than others, of course. MarkLogic's direct support is very responsive and professional. If they can't help immediately, they always have good feedback and are eager to receive information and details to work to replicate the problem. They are quick to escalate major support issues and production show-stopping problems. In addition to MarkLogic's direct support, there are several employees who are very active among the community and many questions and common issues get quick attention from helpful responses to email and StackOverflow questions.
Read full review The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support
Read full review Alternatives Considered We had Fast in place when Microsoft had bought it up and was going to change / deprecate it. One of the biggest advantages of MarkLogic for search actually had to do with the rest of the content pipeline - it allowed us to have it all in one technology. On the NoSQL side, we looked at MongoDB a couple years back. At that time, MarkLogic came in stronger on indexing, transaction reliability, and DR options. For us, that was worth using a commercial product.
Read full review Than
Vertica : Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
Than
Hive :
Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
Read full review Contract Terms and Pricing Model Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.
Read full review Return on Investment MarkLogic reduced the amount of time that the DevOps team needed to dedicate to database updates, as the engineering team was mostly able to easily design and maintain database upgrades without requiring specialists such as database architects on the DevOps side. This capability flowed from the product's speed and the versatility of its XQuery language and libraries. MarkLogic required significant education and buy-in time for the engineering team. Read full review Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost. Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time. Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift. Read full review ScreenShots