DBMS > Apache Druid vs. DolphinDB vs. GridGain vs. IBM Db2 warehouse vs. VoltDB

System Properties Comparison Apache Druid vs. DolphinDB vs. GridGain vs. IBM Db2 warehouse vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Cloud-based data warehousing service

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

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	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

druid.apache.org

www.dolphindb.com

www.gridgain.com

www.ibm.com/products/db2/warehouse

www.voltdb.com

Technical documentation

druid.apache.org/docs/latest/design

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

www.gridgain.com/docs/index.html

docs.voltdb.com

Developer

Apache Software Foundation and contributors

DolphinDB, Inc

GridGain Systems, Inc.

IBM

VoltDB Inc.

Initial release

2012

2018

2007

2014

2010

Current release

29.0.1, April 2024

v2.00.4, January 2022

GridGain 8.5.1

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community version available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

C++

Java, C++, .Net

Java, C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux
OS X
Solaris
Windows

hosted

Linux
OS X

for development

Data scheme

yes

schema-less columns are supported

yes

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

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

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

yes

only a subset of SQL 99

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

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

.NET Client API
JDBC
ODBC
OLE DB

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C#
C++
Java
PHP
Python
Ruby
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

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

PL/SQL, SQL PL

Java

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

yes (replicated cache)

yes

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Administrators, Users, Groups

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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