DBMS > BigObject vs. chDB vs. Ehcache vs. OrientDB

System Properties Comparison BigObject vs. chDB vs. Ehcache vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An embedded SQL OLAP Engine powered by ClickHouse

A widely adopted Java cache with tiered storage options

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Secondary database models

Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

bigobject.io

github.com/chdb-io/chdb

www.ehcache.org

orientdb.org

Technical documentation

docs.bigobject.io

doc.chdb.io

www.ehcache.org/documentation

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

Developer

BigObject, Inc.

Terracotta Inc, owned by Software AG

OrientDB LTD; CallidusCloud; SAP

Initial release

2015

2023

2009

2010

Current release

3.10.0, March 2022

3.2.29, March 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache version 2

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.

Implementation language

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)

server-less

All OS with a Java VM

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

Data scheme

yes

schema-free

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

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

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language, no joins

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JCache

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

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

Java

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

Server-side scripts

Stored procedures

Lua

Java, Javascript

Triggers

yes

Cache Event Listeners

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

relationship in graphs

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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; record level security configurable

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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