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MarkLogic Server

Score9 out of 10

18 Reviews and Ratings

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What is MarkLogic Server?

MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities. The vendor states it is the most secure multi-model database, and it’s deployable in any environment. They state it is an ideal database to power a data hub.

Categories & Use Cases

Key Features

Learn about the best (and worst!) features MarkLogic Server has to offer, as determined by TrustRadius' reviewers.
Based on 18 ratings of MarkLogic Server's features
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Top Performing Features

  • Security

    Security features include authentication against external security mechanisms liker LDAP, Windows Active Directory, and authorization or privilege management. Some NoSQL databases also support encryption.

    Category average: 8.9

  • Performance

    How fast the database performs under data load

    Category average: 9.2

  • Scalability

    NoSQL databases are inherently more stable than relational databases and have built-in support for replication and partitioning of data to support scalability.

    Category average: 9.4

Areas for Improvement

  • Concurrency

    Concurrency is the ability for multiple processes to access or change shared data simultaneously. The greater the number of concurrent user processes that can execute without blocking each other, the greater the concurrency of the database system.

    Category average: 9

  • Data model flexibility

    NoSQL databases do not rely on rely on tables, columns, rows, or schemas to organize and retrieve data, but use use more flexible data models to accommodate the large volume and variety of data being generated by modern applications.

    Category average: 9

  • Deployment model flexibility

    Can be deployed on-premise or in the cloud.

    Category average: 8.9

Reviews

What users are saying about MarkLogic Server.
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Close to perfect NoSQL DB

Incentivized
Prabhudayal AcharyaView profile
Senior Software Engineering in Information Technology at Mindtree (10,001+ employees employees)

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.

Return on Investment

  • Generally speaking, it has positive effects on the product. ROI is kind of ok as the licensing cost is bit higher.
  • Flexible Data Model and Universal Index features of MarkLogic, will help you for sure in achieve quick ROI. For long term you need to think.

Alternatives Considered

MongoDB and HBase

Other Software Used

Jabber, Anaconda

Mark’it with Logic_9553

Incentivized
Lakkireddy Rama Narayana ReddyView profile
Software Engineer in Information Technology at ValueMomentum (1001-5000 employees employees)

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.

Return on Investment

  • ROI is pretty good.
  • It has more positive impact, fewer negative impact.

Alternatives Considered

Hadoop

Other Software Used

MongoDB, Hadoop, Apache Spark

Fantastic if it fits into the use-case

Incentivized
Marcus YoungView profile
Web Application Developer in Information Technology at Aloompa (51-200 employees employees)

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.

Return on Investment

  • It has turned the few people who know how to use it into buckets of knowlege. It's hard to find people to take that knowlege, so the bad effect is that only a few people know how to use and maintain it.

MarkLogic- The Swiss Army Knife of data platforms

Incentivized
Harry Bakken
Principal Consultant in Information Technology at Avalon Consulting, LLC (51-200 employees employees)

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.

Return on Investment

  • We've had customers who have been able to save their organization hundreds of thousands of dollars by preventing duplication of costly processes. Powerful search capabilities into what different business units had available drives better decisions.
  • Ability to receive content in personalized ways has lead to significant new sales opportunities for some of our customers. This personalization includes on-demand publishing of specific articles on specific topics in addition to recommendation engines and shopping cart analysis.
  • One customer that has an extremely advanced application leveraging nearly every feature MarkLogic has to offer found nearly 3:1 cost savings using MarkLogic when they performed an analysis of projected development and maintenance costs to replicate all their functionality on open source stacks.

Usability

Can You Bet on It?

Incentivized
Daniel Davenport
Search Engineer in Engineering at Catalyst Repository Systems (201-500 employees employees)

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.

Return on Investment

  • It took longer than expected to develop our application and get the level of consistent performance necessary. As a result, profit was flat for a couple of years but the benefits are really starting to kick in.

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