TrustRadius Insights for Progress MarkLogic are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Business Problems Solved
MarkLogic is a versatile software used by various industries to implement solutions for their clients. It is utilized in publishing workflows, enterprise search, big data analytics, and the semantic web. Users have praised its powerful geospatial search feature, which efficiently searches locations based on latitude and longitude. MarkLogic's indexing and tokenization techniques contribute to the quick execution of search queries.
Healthcare organizations rely on MarkLogic as a backend store for patient records, enabling storage, retrieval, and updates. By using a micro-services approach with patient matching and search functionality, MarkLogic helps keep patients up-to-date across multiple hospitals. It also serves as a central store for companies dealing with large amounts of data across multiple clusters, providing efficient storage and search capabilities.
In the academic publishing field, MarkLogic is extensively used for end-to-end data flow, including metadata and full-text content. Its newer features like semantics and JavaScript support are leveraged to develop cutting-edge technology.
MarkLogic's multi-model approach, scalability, and exceptional performance in handling XML data make it a preferred choice. It is also employed for reporting purposes with potential for future OLTP and OLAP services. Companies utilize MarkLogic to create DataHubs that consolidate data from various sources, enabling business teams to leverage the data with BI tools.
The technology department at Zynx Health relies on MarkLogic as the primary database layer for clinical decision support analytics. MarkLogic's XML-based solution proves valuable in handling hierarchically structured and semi-structured healthcare data.
MarkLogic is an enterprise NoSQL database server which has multi-model approach, is highly scalable and with exceptional performance. We identified MarkLogic as the best fit because they can load all the data in XML format through different silos and as MarkLogic provides real time services through its RESTful services it can be used as both OLTP and OLAP servers. As of now it is being used only for reporting purposes. We are creating DataHub for our client's various applications serving different portfolios which connect to multiple isolated data silos. Our objective is to bring all that data to DataHub and to create DataMart process for the business team to make use of this data using BI tools. We are using the MarkLogic DataHub Framework which creates documents in a specific envelope pattern. This framework will have set of plugins inside which our code and configurations files will be present.
Pros
MarkLogic is highly scalable and with exceptional performance.
Marklogic provides real time services through its RESTful services it can be used as both OLTP and OLAP servers.
MarkLogic is identified as the best fit because they can load all the data in XML format through different silos.
Cons
How to do complete data profiling on documents loaded in Marklogic database?
Customers need a tools which can be customized to suit their data profiling needs but currently the tools which MarkLogic provides fall short on this requirement.
Unit testing framework which is using only XQuery as the language is lacking some features.
Likelihood to Recommend
MarkLogic is very well suited for all XML and JSON files to get loaded and to derive insights from those huge data sets. It is less appropriate when the number of files is directly proportional to run the query, which should be taken into consideration.
We are searching some restaurants near by any location. We have used the <u>geospatial</u> search feature of MarkLogic. For those who do not know what <u>geopspatial</u> search is the next 3 line is for you. Its search based on geo location using latitude and longitude as parameters. The whole world is divided into some grids by latitude and longitude. Using that feature each and every location can be presented by 2 numbers, one how far and in which direction is it from 00 degree latitude and from 00 longitude. <u>Geospatial</u> search is one of the great features of MarkLogic. It has some in-built features to calculate the distance of a data point from another data point provided that both data have latitude and longitude data present in it. Another features which I like about MarkLogic is - It is really efficient for searching. The time it takes for a search query to run is really less. Thanks to the <b>Indexing</b> and <b>tokenization</b> technique of ML.
Pros
MarkLogic supports fully ACID transaction and I think this is very rare in a NoSQL system.
The recent version of MarkLogic has Integration with Node.js, REST, JSON which has really made the developers life easier to build integrated systems.
MarkLogic provides superb documentation for us. It really helps to understand which features work how. Example is- the whole dedicated website for it. https://docs.marklogic.com/
From the point of infrastructure - Installation, configuration and deployment is very fast. Compared to RDBMS , it's really easy to scale MarkLogic horizontally by adding nodes.
Cons
The licence cost is HIGH.
The amount of space required to store the data seems high hence costly.
The compatibility with legacy system is not yet available. I feel this area needs to be improved very fast.
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.
The technology department at Zynx Health uses MarkLogic as the primary database layer supporting an innovative analytics product for clinical decision support. We had concluded that we wanted an XML-based solution for hierarchically structured and semi-structured data, in part because of the ubiquity of XML-based formats in the healthcare space, but we also wanted enterprise-grade integrity and scaling features, so we decided on MarkLogic.
Pros
MarkLogic's implementation of the XQuery language is fast and versatile, and the additional language features and numerous libraries that they provide out-of-the-box really make it feel like a "batteries included" language, at least within the context of XML and JSON database management.
Despite its enterprise focus, MarkLogic is a very developer-friendly product. All of its administrative features, including provisioning servers, are available through APIs. Most of the functionality one uses from XQuery come in the form of source-included XQuery libraries. I am strongly inclined, generally, to favor open-source solutions, so the focus on freedom and capability for the developer was important to me in this proprietary platform.
MarkLogic is fast. It's much faster than the other XML-based database engines we looked at, and is certainly faster than XML layers bolted on top of relational database engines. The lockless write strategy is great architecture, and it enables the engine to smoothly scale up simultaneous reads and writes. MarkLogic's speed enabled us to perform significant updates on database structure and content as part of our continuous deployment strategy with minimal impact on stability and availability.
Cons
XQuery is a tough language for engineering teams to adopt; it's the world's weirdest pure functional programming language. Once you've crossed over and can see The Matrix, it's clear that the language design is aligned perfectly with the XML querying problem domain, and the fact that it's a Turing-complete programming language rather than just a query domain-specific language (like SQL) enables you to go wherever you need to go with it, which is empowering. But there are areas of obscurity and seeming inconsistency between MarkLogic's lockless write strategy, transaction management and XQuery semantics that all of our developers, at one time or another, ran into, and we only mastered these features after many months with the product and with the help of an expert consultant. It turns out that much of what we learned appears in the copious documentation, but the documentation is SO copious (and, in the area of transaction management, so dense) that none of us had the time to read all of it. This is an area of the product that the documentation should elevate and present, front and center, in a way that is more prescriptive, rather than just descriptive. Give examples showing how developers should solve real problems, and illustrate what the engine is doing.
MarkLogic's pricing, like its feature set, is enterprise-scale. One understands; they're like the Oracle of NoSQL. But the storage restriction on their "free" version basically means that the only way in is full retail, so there are wide categories of companies that would never consider adopting. I wonder if any kind of tiered model might be sustainable for them.
MarkLogic support was quite reasonable in their response time and their general knowledge of the product, but there were certain insights to problems that we really only gained by working with a very knowledgeable consultant that the company recommended for us.
Likelihood to Recommend
If you're looking at MarkLogic because you need an enterprise-grade XML-based database (not just any document store, but specifically XML-based), then the choice is easy. If your needs are more general, and you're looking at MarkLogic as an "enterprise NoSQL" solution, then you should look carefully at the feature set, your current and anticipated needs, and what your options are for achieving "enterprise" goals with other solutions (and engineering investments of your own, including DevOps work).
If MarkLogic still looks good after such analysis, consider whether your team is ready for the investment. Is the team small enough and/or eager enough to buy in, intellectually, to an "exotic" platform like MarkLogic? Can they leave behind the relational mindset and take the time to deeply understand and become productive with XML and the XML ecosystem (e.g., XQuery, XSLT)?
We used it as a backend store for our healthcare records (patient records). We implemented a REST framework for the storage, retrieval and update of records. The rest of the system was a micro-services approach to keep patients up-to-date across multiple hospitals using patient matching and search functionality through MarkLogic. Our company as a whole used it as a central store through our interfaces.
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.
Cons
The management and set up is "too" advanced. It is easy to get started but comes configured wrong out of the box for large stores.
The deployment framework is non-existent. We had to maintain our own framework through Puppet and other means to get it deployed ad-hoc. It's meant to be deployed once, but does not work well with the temporary environment mantra that DevOps aims to achieve.
There is absolutely no way to run tests or automate the testing of REST. We had to roll our own.
The community is lacking for open source. If we needed something we had to write it.
Likelihood to Recommend
In an area where it will be built once and maintained, it shines. If you aim to use CI, temporary environments, or anything else, it is not very effective. Licensing is almost impossible on boxes that are to be created on the fly.
Our company is a business partner with MarkLogic. We have a large practice dedicated to MarkLogic and have worked with many of MarkLogic's largest clients in nearly all verticals implement solutions built on MarkLogic. We have broad expertise across all areas of MarkLogic and help companies architect and deliver robust solutions powered by this database platform. We solved all sorts of business problems including publishing work flows, advanced enterprise search, intense big data analytics, and the semantic web. MarkLogic is a powerful platform for enterprise data hubs (operational data warehouses) and business tools. The "out of the box" search capabilities of this tool are unrivaled.
Pros
MarkLogic does everything well, but search is the "bread and butter" operation. All data is indexed on-the-fly and the API's offer a multitude of ways to create incredibly powerful search applications. The search engine isn't bolted on- it's at the core of the database. Search suggestion, relevance, advanced grammar, spell correction (did you mean?), paginated search over massive numbers of records, etc. is all at the fingertips of the developer. The database scales to massive size and yet search returns sub-second results for the most complex search parameters.
High availability, disaster recovery, and scaling is handled incredibly well. In the AWS cloud, it is trivial to set up a MarkLogic system to elastically scale with data and request volume- truly elastic, adding nodes and removing them as needed. Databases can replicate to a remote datacenter in real-time to provide instant cut-over for datacenter loss. Clustered servers provide highly available replication of data to instantly recover from node failures.
Security is increasingly important as data takes center stage in an enterprise. MarkLogic's role-based security is baked in to every query. This is battle-hardened content control.
Flexibility is unrivaled. Any data can be stored reliably and securely in the MarkLogic database. Records can be stored as text, XML, JSON, or binary. All text, XML, and JSON is instantly indexed and the various strategies for indexing are easy to configured and well documented. MarkLogic is also a powerful semantic triple store. Unlike any other NoSQL solution, MarkLogic can handle full documents, graphs, key-value pairs, binaries, etc. in a single database, providing powerful and unique ways of combining enterprise data.
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.
Likelihood to Recommend
There are few situations where MarkLogic is not well suited, however there's certainly use cases where it is using a missile to swat a fly. Important considerations in the selection process include:
<ul><li>Mission critical nature of your data</li><li>Complexity of your data- do you have polystructured data?</li><li>Data volume- MarkLogic can handle few records, but it's really meant to house significant volumes of data.</li><li>Composition of your development team</li><li>Lifecycle of your system</li></ul>
MarkLogic is the database engine at the core of my company's flagship product. We use it to store and search approximately 100 TB of data across approximately 10 separate clusters. It most cases we can produce search results with amazing speed.
Pros
MarkLogic is fast and flexible. The data does not have to be structured (particularly in advance).
MarkLogic is a combination database, search engine, and application server. As a database, it is ACID compliant which is absolutely essential for mission critical production applications.
MarkLogic is dependable, in almost all cases recovers by itself, and is relatively easy to administer.
Cons
MarkLogic is not cheap, either for the software itself, the hardware to run it on, or the investment in learning necessary to use it effectively. While MarkLogic has gone to great pains to add multiple interfaces so that a deep understanding of XQuery is theoretically not necessary, I feel XQuery is essential to understanding the product well enough to use it in production applications.
Specifically, it is my understanding that switching database contexts is expensive in terms of performance. There could be be a improvement in the ability to query across databases, or even across clusters, that could drive greater flexibility in design decisions.
The security model definitely could be improved to facilitate sharing users, roles, and permissions across clusters. Building your own security model to allow users access to data on different clusters is very complex and leads to a number of performance issues.
Likelihood to Recommend
The first question is [around] how rigidly your data is structured. If it is well structured and non-volatile, an RDBMS database is an alternative. If it is not well structured or the structure changes, a NoSQL database should definitely be considered. However, there is no free lunch. NoSQL requires a different mindset and skill set. It is easy to set up a prototype that runs but much harder to design it to really take advantage of the speed it is capable of. To be able to query 10TB of data and get an accurate subsecond response is a thing of beauty. To be able to do it consistently requires a lot of deep technical knowledge. People with deep technical knowledge of MarkLogic, NoSQL, XML, and XQuery are in great demand. You will need a good plan to find, grow, and keep such talent.
MarkLogic is used the most by the academic publishing unit. There it is used for an end to end data flow for the metadata and full text of our academic publishing products (PsycINFO database, Peer reviewed journals, Books, Psychological Tests and Measures). In addition, we use some of the newer capabilities, such as semantics and javascript support, for our "labs" where we develop cutting edge technology for our content.
Pros
Indexing is a major strength of MarkLogic. The out-of-the-box configuration is set up to handle a combination of text and fielded data. The indexing is also highly configurable. Those configuration options are at the heart of a lot of our high-volume, high-performance applications.
The industrial strength transactions and security are also a strength, particularly when we are dealing with user-created intellectual property.
The engineering support is a strength. They are big enough to have a really strong support and engineering staff, but small enough so that a medium-sized customer has access to it. They are very responsive to questions and problem reports.
The ability to move easily among XML and JSON is a strength.
Cons
There is a steep learning curve to learn to use this tool, particularly the xquery and extensive associated API. The more recent releases and features have been responsive to this concern, but some of the core features still take some learning.
The javascript implementation is new and there are still some spots where it needs to be made fully compliant with standards and conventions, such as file extensions
Likelihood to Recommend
We first purchased MarkLogic licenses in 2008, when we were a publisher with lots of XML and they were an XML database. That was a pretty clear fit. Since then, they have moved into the mainstream of NoSQL and so have we. I think they would be a good fit for anyone that has NoSQL needs that also require industrial strength transaction safety, ability to scale, and that sort of feature. They are commercial, not open source, so if someone is committed to the whole stack being open source, then this is not a good fit.
