DBMS > Google BigQuery vs. InfluxDB vs. LMDB vs. Lovefield vs. OpenEdge

System Properties Comparison Google BigQuery vs. InfluxDB vs. LMDB vs. Lovefield vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

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

Embeddable relational database for web apps written in pure JavaScript

Application development environment with integrated database management system

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

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

google.github.io/lovefield

www.progress.com/openedge

Technical documentation

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

www.lmdb.tech/doc

github.com/google/lovefield/blob/master/docs/spec_index.md

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Google

Symas

Google

Progress Software Corporation

Initial release

2010

2013

2011

2014

1984

Current release

2.7.6, April 2024

0.9.32, January 2024

2.1.12, February 2017

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

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

JavaScript

Server operating systems

hosted

Linux
OS X

through Homebrew

Linux
Unix
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL-like query language

via JavaScript builder pattern

yes

close to SQL 92

APIs and other access methods

RESTful HTTP/JSON API

HTTP API
JSON over UDP

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.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

JavaScript

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

none

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

using MemoryDB

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

Users and groups

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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