DBMS > DolphinDB vs. Elasticsearch vs. HEAVY.AI vs. NSDb

System Properties Comparison DolphinDB vs. Elasticsearch vs. HEAVY.AI vs. NSDb

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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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

www.dolphindb.com

www.elastic.co/elasticsearch

github.com/heavyai/heavydb
www.heavy.ai

nsdb.io

Technical documentation

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

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.heavy.ai

nsdb.io/Architecture

Developer

DolphinDB, Inc

Elastic

HEAVY.AI, Inc.

Initial release

2018

2010

2016

2017

Current release

v2.00.4, January 2022

8.6, January 2023

5.10, January 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

Elastic License

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++ and CUDA

Java, Scala

Server operating systems

Linux
Windows

All OS with a Java VM

Linux

Linux
macOS

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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.

Secondary indexes

yes

All search fields are automatically indexed

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

gRPC
HTTP REST
WebSocket

Supported programming languages

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

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

yes

Memcached and Redis integration

yes

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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