DBMS > Apache Druid vs. Geode vs. HugeGraph vs. JSqlDb

System Properties Comparison Apache Druid vs. Geode vs. HugeGraph 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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A fast-speed and highly-scalable Graph DBMS

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Graph 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	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

druid.apache.org

geode.apache.org

github.com/hugegraph
hugegraph.apache.org

jsqldb.org (offline)

Technical documentation

druid.apache.org/docs/latest/design

geode.apache.org/docs

hugegraph.apache.org/docs

Developer

Apache Software Foundation and contributors

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Baidu

Konrad von Backstrom

Initial release

2012

2002

2018

Current release

29.0.1, April 2024

1.1, February 2017

0.9

0.8, December 2018

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

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

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Unix

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

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.

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

SQL for querying

SQL-like query language (OQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java Client API
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

Groovy
Java
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

functions in JavaScript

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

yes, on a single node

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

Access rights per client and object definable

Users, roles and permissions

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