DBMS > BoltDB vs. ClickHouse vs. GridGain vs. JanusGraph vs. JSqlDb

System Properties Comparison BoltDB vs. ClickHouse vs. GridGain vs. JanusGraph vs. JSqlDb

Editorial information provided by DB-Engines

Name

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

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Graph DBMS

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Website

github.com/boltdb/bolt

clickhouse.com

www.gridgain.com

janusgraph.org

jsqldb.org (offline)

Technical documentation

clickhouse.com/docs

www.gridgain.com/docs/index.html

docs.janusgraph.org

Developer

Clickhouse Inc.

GridGain Systems, Inc.

Linux Foundation; originally developed as Titan by Aurelius

Konrad von Backstrom

Initial release

2013

2016

2007

2017

2018

Current release

v24.4.1.2088-stable, May 2024

GridGain 8.5.1

0.6.3, February 2023

0.8, December 2018

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

Open Source

Apache 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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
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ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

Java, C++, .Net

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

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

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
C++
Java
PHP
Python
Ruby
Scala

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

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

yes

functions in JavaScript

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes (replicated cache)

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Security Hooks for custom implementations

User authentification and security via Rexster Graph Server

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