DBMS > ClickHouse vs. JanusGraph vs. SAP Adaptive Server vs. SAP SQL Anywhere vs. YottaDB

System Properties Comparison ClickHouse vs. JanusGraph vs. SAP Adaptive Server vs. SAP SQL Anywhere vs. YottaDB

Editorial information provided by DB-Engines

Name

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 Graph DBMS optimized for distributed clusters

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Time Series DBMS

Spatial DBMS

with Boeing's Spatial Query Server

Relational DBMS

using the Octo plugin

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

clickhouse.com

janusgraph.org

www.sap.com/products/technology-platform/sybase-ase.html

www.sap.com/products/technology-platform/sql-anywhere.html

yottadb.com

Technical documentation

clickhouse.com/docs

docs.janusgraph.org

help.sap.com/docs/SAP_ASE

help.sap.com/docs/SAP_SQL_Anywhere

yottadb.com/resources/documentation

Developer

Clickhouse Inc.

Linux Foundation; originally developed as Titan by Aurelius

SAP, Sybase

SAP

formerly Sybase

YottaDB, LLC

Initial release

2016

2017

1987

1992

2001

Current release

v24.4.1.2088-stable, May 2024

0.6.3, February 2023

16.0

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0

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++

Java

C and C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Docker
Linux

Data scheme

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)

yes

by using the Octo plugin

APIs and other access methods

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
HTTP API
JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

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

Clojure
Java
Python

C
C++
Cobol
Java
Java
Perl
PHP
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Java and Transact-SQL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

yes

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

optimistic locking

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

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.

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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