DBMS > AgensGraph vs. AlaSQL vs. Google BigQuery vs. LeanXcale vs. RavenDB

System Properties Comparison AgensGraph vs. AlaSQL vs. Google BigQuery vs. LeanXcale vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

JavaScript DBMS library

Large scale data warehouse service with append-only tables

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Graph DBMS
Relational DBMS

Document store
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.07
Rank	#329	Overall
	#33	Graph DBMS
	#148	Relational DBMS

Score	0.56
Rank	#226	Overall
	#35	Document stores
	#108	Relational DBMS

Score	50.03
Rank	#24	Overall
	#16	Relational DBMS

Score	0.15
Rank	#299	Overall
	#44	Key-value stores
	#138	Relational DBMS

Score	3.89
Rank	#90	Overall
	#17	Document stores

Website

bitnine.net

alasql.org

cloud.google.com/bigquery

www.leanxcale.com

ravendb.net

Technical documentation

bitnine.net/documentation

github.com/agershun/alasql

cloud.google.com/bigquery/docs

ravendb.net/docs

Developer

Bitnine Global Inc.

Andrey Gershun & Mathias R. Wulff

Google

LeanXcale

Hibernating Rhinos

Initial release

2016

2014

2010

2015

2010

Current release

2.1, December 2018

5.3, November 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT-License

commercial

Open Source

AGPL version 3, commercial license available

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

Linux
OS X
Windows

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

hosted

Linux
macOS
Raspberry Pi
Windows

Data scheme

depending on used data model

schema-free

yes

schema-free

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

yes

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

through Apache Derby

SQL-like query language (RQL)

APIs and other access methods

Cypher Query Language
JDBC

JavaScript API

RESTful HTTP/JSON API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

.NET Client API
Java Client API
Python Client API
RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
Java
Scala

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

MapReduce functions can be defined in Linq

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

Since BigQuery is designed for querying data

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

Access control on document level using the Authorization Bundle

More information provided by the system vendor

Specific characteristics

Full ACID and full SQL operational database with analytical queries over operational...
» more

RavenDB is the pioneer NoSQL Document Database that is fully transactional (ACID)...
» more

Competitive advantages

Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more

RavenDB is easy to setup and secure. You can do it in a matter of minutes . Easy...
» more

Typical application scenarios

Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more

IoT for Edge Deployments Fraud Detection Recommendation Engines Product Catalogs...
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Key customers

banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more

Toyota, Capgemini, Vodafone, Medicaid, Asos, Nomura, RMS Automotive, MSNBC, Pluralsight,...
» more

Market metrics

15 beta testers
» more

2 million+ downloads 1000+ customers including Fortune 500 large enterprises
» more

Licensing and pricing models

annual fee covering license and support based on number of physical cores
» more

RavenDB is available on-premise and in the cloud. RavenDB Cloud is available on AWS...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.