DBMS > DolphinDB vs. GBase vs. Hypertable vs. Ignite vs. Snowflake

System Properties Comparison DolphinDB vs. GBase vs. Hypertable vs. Ignite vs. Snowflake

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

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.

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Time Series DBMS

Relational DBMS

Wide column store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

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

apacheignite.readme.io/docs

docs.snowflake.net/manuals/index.html

Developer

DolphinDB, Inc

General Data Technology Co., Ltd.

Hypertable Inc.

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2018

2004

2009

2015

2014

Current release

v2.00.4, January 2022

GBase 8a, GBase 8s, GBase 8c

0.9.8.11, March 2016

Apache Ignite 2.6

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

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++

C, Java, Python

C++

C++, Java, .Net

Server operating systems

Linux
Windows

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

C++ API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

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

User concepts

Access control

Administrators, Users, Groups

yes

Security Hooks for custom implementations

Users with fine-grained authorization concept, user roles and pluggable authentication

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