DBMS > ClickHouse vs. GridGain vs. LevelDB vs. RDF4J vs. Titan

System Properties Comparison ClickHouse vs. GridGain vs. LevelDB vs. RDF4J vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

RDF store

Graph DBMS

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

clickhouse.com

www.gridgain.com

github.com/google/leveldb

rdf4j.org

github.com/thinkaurelius/titan

Technical documentation

clickhouse.com/docs

www.gridgain.com/docs/index.html

github.com/google/leveldb/blob/main/doc/index.md

rdf4j.org/documentation

github.com/thinkaurelius/titan/wiki

Developer

Clickhouse Inc.

GridGain Systems, Inc.

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Aurelius, owned by DataStax

Initial release

2016

2007

2011

2004

2012

Current release

v24.4.1.2088-stable, May 2024

GridGain 8.5.1

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java, C++, .Net

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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

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
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes (replicated cache)

none

yes

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory storage is supported as well

yes

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

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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