DBMS > Apache Impala vs. DolphinDB vs. GBase vs. MySQL vs. YDB

System Properties Comparison Apache Impala vs. DolphinDB vs. GBase vs. MySQL vs. YDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Widely used open source RDBMS

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store
Relational DBMS

Secondary database models

Document store

Relational DBMS

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

impala.apache.org/impala-docs.html

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

dev.mysql.com/doc

ydb.tech/en/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DolphinDB, Inc

General Data Technology Co., Ltd.

Oracle

since 2010, originally MySQL AB, then Sun

Yandex

Initial release

2013

2018

2004

1995

2019

Current release

4.1.0, June 2022

v2.00.4, January 2022

GBase 8a, GBase 8s, GBase 8c

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community version available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C, Java, Python

C and C++

Server operating systems

Linux

Linux
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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-like DML and DDL statements

SQL-like query language

Standard with numerous extensions

yes

with proprietary extensions

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

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

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Administrators, Users, Groups

yes

Users with fine-grained authorization concept

no user groups or roles

Access rights defined for Yandex Cloud users

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