DBMS > BigObject vs. ClickHouse vs. Oracle Coherence vs. SAP SQL Anywhere vs. Yaacomo

System Properties Comparison BigObject vs. ClickHouse vs. Oracle Coherence vs. SAP SQL Anywhere vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Analytic DBMS for real-time computations and queries

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.

Oracles in-memory data grid solution

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

bigobject.io

clickhouse.com

www.oracle.com/java/coherence

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

yaacomo.com

Technical documentation

docs.bigobject.io

clickhouse.com/docs

docs.oracle.com/en/middleware/standalone/coherence

help.sap.com/docs/SAP_SQL_Anywhere

Developer

BigObject, Inc.

Clickhouse Inc.

Oracle

SAP

formerly Sybase

Q2WEB GmbH

Initial release

2015

2016

2007

1992

2009

Current release

v24.4.1.2088-stable, May 2024

14.1, August 2023

17, July 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
macOS

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

JCache
JPA
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

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

.Net
C++
Java

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

Server-side scripts

Stored procedures

Lua

yes

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

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes, with selectable consistency level

Source-replica replication

Database mirroring

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

optionally

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.

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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