DBMS > AlaSQL vs. H2 vs. HugeGraph vs. Hypertable vs. Transwarp Hippo

System Properties Comparison AlaSQL vs. H2 vs. HugeGraph vs. Hypertable vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

JavaScript DBMS library

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

A fast-speed and highly-scalable Graph DBMS

An open source BigTable implementation based on distributed file systems such as Hadoop

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store
Relational DBMS

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	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

alasql.org

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

github.com/AlaSQL/alasql

www.h2database.com/html/main.html

hugegraph.apache.org/docs

Developer

Andrey Gershun & Mathias R. Wulff

Thomas Mueller

Baidu

Hypertable Inc.

Initial release

2014

2005

2018

2009

2023

Current release

2.2.220, July 2023

0.9

0.9.8.11, March 2016

1.0, May 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

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

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

C++

Server operating systems

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

All OS with a Java VM

Linux
macOS
Unix

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

also supports composite index and range index

restricted

only exact value or prefix value scans

SQL

Support of SQL

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

yes

APIs and other access methods

JavaScript API

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

C++ API
Thrift

RESTful HTTP API

Supported programming languages

JavaScript

Java

Groovy
Java
Python

C++
Java
Perl
PHP
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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, multi-version concurrency control (MVCC)

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

Users, roles and permissions

Role based access control and fine grained access rights

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

全面升级！Apache HugeGraph 1.2.0版本发布_apach hugegraph
27 February 2024, blog.csdn.net

HugeGraph 部署和Hubble1.0.0的数据导入Bug修复_hugegraph-hubble导入数据
18 October 2023, blog.csdn.net

provided by Google News

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

Decorate your Windows XP with Hyperdesk
30 July 2008, CNET

The Collective: Customize Your Computer & Your Phone With Star Trek
18 March 2009, TrekMovie

NoSQL Market: A well-defined technological growth map with an impact-analysis
19 June 2020, Inter Press Service

provided by Google News

Share this page