DBMS > ClickHouse vs. Graph Engine vs. OrientDB vs. Sqrrl vs. Trafodion

System Properties Comparison ClickHouse vs. Graph Engine vs. OrientDB vs. Sqrrl vs. Trafodion

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. 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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Multi-model DBMS (Document, Graph, Key/Value)

Adaptable, secure NoSQL built on Apache Accumulo

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Document store
Graph DBMS
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational 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	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

sqrrl.com

Technical documentation

clickhouse.com/docs

www.graphengine.io/docs/manual

www.orientdb.com/docs/last/index.html

trafodion.apache.org/documentation.html

Developer

Clickhouse Inc.

Microsoft

OrientDB LTD; CallidusCloud; SAP

Amazon

originally Sqrrl Data, Inc.

Apache Software Foundation, originally developed by HP

Initial release

2016

2010

2012

2014

Current release

v24.4.1.2088-stable, May 2024

3.2.29, March 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

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.

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Implementation language

C++

.NET and C

Java

C++, Java

Server operating systems

FreeBSD
Linux
macOS

.NET

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language, no joins

yes

APIs and other access methods

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

RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

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++
F#
Visual Basic

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java, Javascript

Java Stored Procedures

Triggers

Hooks

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

selectable replication factor

making use of Hadoop

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

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.

Access rights for users and roles; record level security configurable

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

fine grained access rights according to SQL-standard

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