DBMS > DolphinDB vs. Ehcache vs. MarkLogic vs. Postgres-XL vs. Vertica

System Properties Comparison DolphinDB vs. Ehcache vs. MarkLogic vs. Postgres-XL vs. Vertica

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A widely adopted Java cache with tiered storage options

Operational and transactional Enterprise NoSQL database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Time Series DBMS
Vector DBMS

Key-value store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Column oriented

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.dolphindb.com

www.ehcache.org

www.progress.com/marklogic

www.postgres-xl.org

www.vertica.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.ehcache.org/documentation

www.progress.com/marklogic/documentation

www.postgres-xl.org/documentation

vertica.com/documentation

Developer

DolphinDB, Inc

Terracotta Inc, owned by Software AG

MarkLogic Corp.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2018

2009

2001

2014

since 2012, originally named StormDB

2005

Current release

v2.00.4, January 2022

3.10.0, March 2022

11.0, December 2022

10 R1, October 2018

12.0.3, January 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

Mozilla public license

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Windows

Linux
macOS

Linux

Data scheme

yes

schema-free

Schema can be enforced

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language

yes

SQL92

yes

distributed, parallel query execution

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JCache

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Cache Event Listeners

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

by using Terracotta Server

Sharding

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

yes, with Range Indexes

User concepts

Access control

Administrators, Users, Groups

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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Related products and services

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More resources

Conferences, events and webinars

more DBMS events

Progress MarkLogic World
Washington DC, 23-25 September 2024

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