DBMS > AlaSQL vs. Cloudflare Workers KV vs. Google BigQuery vs. GridGain vs. XTDB

System Properties Comparison AlaSQL vs. Cloudflare Workers KV vs. Google BigQuery vs. GridGain vs. XTDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Large scale data warehouse service with append-only tables

GridGain is an in-memory computing platform, built on Apache Ignite

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Document store

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

alasql.org

www.cloudflare.com/developer-platform/workers-kv

cloud.google.com/bigquery

www.gridgain.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

github.com/AlaSQL/alasql

developers.cloudflare.com/kv/api

cloud.google.com/bigquery/docs

www.gridgain.com/docs/index.html

www.xtdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Cloudflare

Google

GridGain Systems, Inc.

Juxt Ltd.

Initial release

2014

2018

2010

2007

2019

Current release

GridGain 8.5.1

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

MIT License

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

Java, C++, .Net

Clojure

Server operating systems

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

hosted

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

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

yes

ANSI-99 for query and DML statements, subset of DDL

limited SQL, making use of Apache Calcite

APIs and other access methods

JavaScript API

HTTP REST
Proprietary protocol

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST
JDBC

Supported programming languages

JavaScript

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes (replicated cache)

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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)

Security Hooks for custom implementations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.