DBMS > Apache Druid vs. Databend vs. GridGain vs. JSqlDb

System Properties Comparison Apache Druid vs. Databend vs. GridGain vs. JSqlDb

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store
Object oriented DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Website

druid.apache.org

github.com/datafuselabs/databend
www.databend.com

www.gridgain.com

jsqldb.org (offline)

Technical documentation

druid.apache.org/docs/latest/design

docs.databend.com

www.gridgain.com/docs/index.html

Developer

Apache Software Foundation and contributors

Databend Labs

GridGain Systems, Inc.

Konrad von Backstrom

Initial release

2012

2021

2007

2018

Current release

29.0.1, April 2024

1.0.59, April 2023

GridGain 8.5.1

0.8, December 2018

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

Open Source

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

Java

Rust

Java, C++, .Net

Server operating systems

Linux
OS X
Unix

hosted
Linux
macOS

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

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 for querying

yes

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

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
RESTful HTTP API

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

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

functions in JavaScript

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

using RocksDB

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

Users with fine-grained authorization concept, user roles

Security Hooks for custom implementations

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