HBase vs MarkLogic vs TokuMX

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HBase
HBase

209
176
+ 1
12
MarkLogic
MarkLogic

16
19
+ 1
23
TokuMX
TokuMX

6
8
+ 1
3
- No public GitHub repository available -

What is 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.

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 TokuMX?

TokuMX is a drop-in replacement for MongoDB, and offers 20X performance improvements, 90% reduction in database size, and support for ACID transactions with MVCC. TokuMX has the same binaries, supports the same drivers, data model, and features of MongoDB, because it shares much of its code with MongoDB.
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Why do developers choose MarkLogic?
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        What companies use HBase?
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        What are some alternatives to HBase, MarkLogic, and TokuMX?
        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.
        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.
        Hadoop
        The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
        Druid
        Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
        Apache Hive
        Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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        How developers use HBase, MarkLogic, and TokuMX
        Avatar of Pinterest
        Pinterest uses HBaseHBase

        The final output is inserted into HBase to serve the experiment dashboard. We also load the output data to Redshift for ad-hoc analysis. For real-time experiment data processing, we use Storm to tail Kafka and process data in real-time and insert metrics into MySQL, so we could identify group allocation problems and send out real-time alerts and metrics.

        Avatar of Axibase
        Axibase uses HBaseHBase
        • Raw storage engine
        • Replication
        • Fault-tolerance
        Avatar of Mehdi TAZI
        Mehdi TAZI uses HBaseHBase

        Range scan and HDFS Buffering system

        Avatar of anerudhbalaji
        anerudhbalaji uses HBaseHBase

        Primary datastore

        How much does HBase cost?
        How much does MarkLogic cost?
        How much does TokuMX cost?
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