DBMS > Apache Drill vs. DolphinDB vs. Graph Engine vs. searchxml

System Properties Comparison Apache Drill vs. DolphinDB vs. Graph Engine vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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 in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Relational DBMS

Time Series DBMS

Graph DBMS
Key-value store

Native XML DBMS
Search engine

Secondary database models

Relational DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

drill.apache.org

www.dolphindb.com

www.graphengine.io

www.searchxml.net/category/products

Technical documentation

drill.apache.org/docs

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

www.graphengine.io/docs/manual

www.searchxml.net/support/handouts

Developer

Apache Software Foundation

DolphinDB, Inc

Microsoft

informationpartners gmbh

Initial release

2012

2018

2010

2015

Current release

1.20.3, January 2023

v2.00.4, January 2022

1.0

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community version available

Open Source

MIT License

commercial

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++

.NET and C

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

.NET

Windows

Data scheme

schema-free

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C++

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

C#
C++
F#
Visual Basic

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Administrators, Users, Groups

Domain, group and role-based access control at the document level and for application services

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

provided by Google News

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

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