DBMS > EventStoreDB vs. Faircom EDGE vs. Google Cloud Bigtable vs. Oracle NoSQL vs. TimesTen

System Properties Comparison EventStoreDB vs. Faircom EDGE vs. Google Cloud Bigtable vs. Oracle NoSQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

In-Memory RDBMS compatible to Oracle

Primary database model

Event Store

Key-value store
Relational DBMS

Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

www.eventstore.com

www.faircom.com/products/faircom-edge

cloud.google.com/bigtable

www.oracle.com/database/nosql/technologies/nosql

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developers.eventstore.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

cloud.google.com/bigtable/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.oracle.com/database/timesten-18.1

Developer

Event Store Limited

FairCom Corporation

Google

Oracle

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

1979

2015

2011

1998

Current release

21.2, February 2021

V3, October 2020

23.3, December 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

commercial

Restricted, free version available

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

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

ANSI C, C++

Java

Server operating systems

Linux
Windows

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

optional

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

yes

ANSI SQL queries

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Internal replication in Colossus, and regional replication between two clusters in different zones

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Atomic single-row operations

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

User concepts

Access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

fine grained access rights according to SQL-standard

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