DBMS > AlaSQL vs. GridGain vs. H2 vs. Snowflake vs. XTDB

System Properties Comparison AlaSQL vs. GridGain vs. H2 vs. Snowflake vs. XTDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

Technical documentation

github.com/AlaSQL/alasql

www.gridgain.com/docs/index.html

www.h2database.com/html/main.html

docs.snowflake.net/manuals/index.html

www.xtdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

GridGain Systems, Inc.

Thomas Mueller

Snowflake Computing Inc.

Juxt Ltd.

Initial release

2014

2007

2005

2014

2019

Current release

GridGain 8.5.1

2.2.220, July 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java, C++, .Net

Java

Clojure

Server operating systems

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

Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

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

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JavaScript API

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

JDBC
ODBC

CLI Client
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

Java

JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

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

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

yes

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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