DBMS > Hypertable vs. MarkLogic vs. Pinecone

System Properties Comparison Hypertable vs. MarkLogic vs. Pinecone

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

Operational and transactional Enterprise NoSQL database

A managed, cloud-native vector database

Primary database model

Wide column store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.42
Rank	#67	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	3.13
Rank	#88	Overall
	#3	Vector DBMS

Website

www.progress.com/marklogic

www.pinecone.io

Technical documentation

www.progress.com/marklogic/documentation

docs.pinecone.io/docs/overview

Developer

Hypertable Inc.

MarkLogic Corp.

Pinecone Systems, Inc

Initial release

2009

2001

2019

Current release

0.9.8.11, March 2016

11.0, December 2022

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Windows

hosted

Data scheme

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

yes

String, Number, Boolean

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL92

APIs and other access methods

C++ API
Thrift

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

RESTful HTTP API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Python

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, with Range Indexes

User concepts

Access control

Role-based access control at the document and subdocument levels

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Conferences, events and webinars

more DBMS events

Progress MarkLogic World
Washington DC, 23-25 September 2024

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