DBMS > CouchDB vs. Google BigQuery vs. LMDB vs. OpenEdge vs. TigerGraph

System Properties Comparison CouchDB vs. Google BigQuery vs. LMDB vs. OpenEdge vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Large scale data warehouse service with append-only tables

A high performant, light-weight, embedded key-value database library

Application development environment with integrated database management system

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

couchdb.apache.org

cloud.google.com/bigquery

www.symas.com/symas-embedded-database-lmdb

www.progress.com/openedge

www.tigergraph.com

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigquery/docs

www.lmdb.tech/doc

documentation.progress.com/output/ua/OpenEdge_latest

docs.tigergraph.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

Symas

Progress Software Corporation

Initial release

2005

2010

2011

1984

2017

Current release

3.3.3, December 2023

0.9.32, January 2024

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

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

via views

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Progress proprietary ABL (Advanced Business Language)

C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

atomic operations within a single document possible

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

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 can be defined per database

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

Google Cloud Identity & Access Management (IAM)

Users and groups

Role-based access control

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