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MarkLogic

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RethinkDB

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+ 1
307
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MarkLogic vs RethinkDB: What are the differences?

MarkLogic: Schema-agnostic Enterprise NoSQL database technology, coupled w/ powerful search & flexible application services. MarkLogic is the only Enterprise NoSQL database, bringing all the features you need into one unified system: a document-centric, schema-agnostic, structure-aware, clustered, transactional, secure, database server with built-in search and a full suite of application services; RethinkDB: JSON. Scales to multiple machines with very little effort. Open source. RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

MarkLogic and RethinkDB belong to "Databases" category of the tech stack.

Some of the features offered by MarkLogic are:

  • Search and Query
  • ACID Transactions
  • High Availability and Disaster Recovery

On the other hand, RethinkDB provides the following key features:

  • JSON data model and immediate consistency.
  • Distributed joins, subqueries, aggregation, atomic updates.
  • Secondary, compound, and arbitrarily computed indexes.

"RDF Triples" is the top reason why over 3 developers like MarkLogic, while over 46 developers mention "Powerful query language" as the leading cause for choosing RethinkDB.

RethinkDB is an open source tool with 22.4K GitHub stars and 1.74K GitHub forks. Here's a link to RethinkDB's open source repository on GitHub.

Advice on MarkLogic and RethinkDB
Needs advice
on
HadoopHadoopMarkLogicMarkLogic
and
SnowflakeSnowflake

For a property and casualty insurance company, we currently use MarkLogic and Hadoop for our raw data lake. Trying to figure out how snowflake fits in the picture. Does anybody have some good suggestions/best practices for when to use and what data to store in Mark logic versus Snowflake versus a hadoop or all three of these platforms redundant with one another?

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Needs advice
on
HadoopHadoopMarkLogicMarkLogic
and
SnowflakeSnowflake

for property and casualty insurance company we current Use marklogic and Hadoop for our raw data lake. Trying to figure out how snowflake fits in the picture. Does anybody have some good suggestions/best practices for when to use and what data to store in Mark logic versus snowflake versus a hadoop or all three of these platforms redundant with one another?

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Replies (1)
Ivo Dinis Rodrigues
none of you bussines at Marklogic · | 1 upvotes · 22.2K views
Recommends

As i see it, you can use Snowflake as your data warehouse and marklogic as a data lake. You can add all your raw data to ML and curate it to a company data model to then supply this to Snowflake. You could try to implement the dw functionality on marklogic but it will just cost you alot of time. If you are using Aws version of Snowflake you can use ML spark connector to access the data. As an extra you can use the ML also as an Operational report system if you join it with a Reporting tool lie PowerBi. With extra apis you can also provide data to other systems with ML as source.

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Decisions about MarkLogic and RethinkDB

I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.

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Pros of MarkLogic
Pros of RethinkDB
  • 5
    RDF Triples
  • 3
    JSON
  • 3
    Marklogic is absolutely stable and very fast
  • 3
    REST API
  • 3
    JavaScript
  • 3
    Enterprise
  • 2
    Semantics
  • 2
    Multi-model DB
  • 1
    Bitemporal
  • 1
    Tiered Storage
  • 48
    Powerful query language
  • 46
    Excellent dashboard
  • 42
    JSON
  • 41
    Distributed database
  • 38
    Open source
  • 25
    Reactive
  • 16
    Atomic updates
  • 15
    Joins
  • 9
    MVCC concurrency
  • 9
    Hadoop-style map/reduce
  • 4
    Geospatial support
  • 4
    Real-time, open-source, scalable
  • 2
    YC Company
  • 2
    A NoSQL DB with joins
  • 2
    Great Admin UI
  • 2
    Changefeeds: no polling needed to get updates
  • 2
    Fast, easily scalable, great customer support

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118
3.9K
5.1K
1.4K
1.4K
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What is MarkLogic?

MarkLogic is the only Enterprise NoSQL database, bringing all the features you need into one unified system: a document-centric, schema-agnostic, structure-aware, clustered, transactional, secure, database server with built-in search and a full suite of application services.

What is RethinkDB?

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Need advice about which tool to choose?Ask the StackShare community!

What companies use MarkLogic?
What companies use RethinkDB?
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What tools integrate with MarkLogic?
What tools integrate with RethinkDB?

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What are some alternatives to MarkLogic and RethinkDB?
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Neo4j
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
HBase
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
See all alternatives