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IBM DB2 vs MarkLogic: What are the differences?
Developers describe IBM DB2 as "A family of database server products developed by IBM". DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs. On the other hand, MarkLogic is detailed as "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.
IBM DB2 and MarkLogic can be categorized as "Databases" tools.
"Rock solid and very scalable" is the primary reason why developers consider IBM DB2 over the competitors, whereas "RDF Triples" was stated as the key factor in picking MarkLogic.
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?
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?
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.
Pros of IBM DB2
- Rock solid and very scalable7
- BLU Analytics is amazingly fast5
- Native XML support2
- Secure by default2
- Easy2
- Best performance1
Pros of MarkLogic
- RDF Triples5
- JSON3
- Marklogic is absolutely stable and very fast3
- REST API3
- JavaScript3
- Enterprise3
- Semantics2
- Multi-model DB2
- Bitemporal1
- Tiered Storage1
