DBMS > BigObject vs. Ehcache vs. Google BigQuery vs. OrientDB

System Properties Comparison BigObject vs. Ehcache vs. Google BigQuery vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

Large scale data warehouse service with append-only tables

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

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

Website

bigobject.io

www.ehcache.org

cloud.google.com/bigquery

orientdb.org

Technical documentation

docs.bigobject.io

www.ehcache.org/documentation

cloud.google.com/bigquery/docs

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

Developer

BigObject, Inc.

Terracotta Inc, owned by Software AG

Google

OrientDB LTD; CallidusCloud; SAP

Initial release

2015

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; commercial licenses available

commercial

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

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)

All OS with a Java VM

hosted

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

Data scheme

yes

schema-free

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

yes

SQL-like query language, no joins

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JCache

RESTful HTTP/JSON API

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

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Lua

user defined functions

in JavaScript

Java, Javascript

Triggers

yes

Cache Event Listeners

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

none

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)

Immediate Consistency

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

Since BigQuery is designed for querying data

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles; record level security configurable

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