DBMS > GBase vs. H2 vs. HEAVY.AI vs. TimescaleDB vs. Transwarp Hippo

System Properties Comparison GBase vs. H2 vs. HEAVY.AI vs. TimescaleDB vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

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

Primary database model

Relational DBMS

Time Series DBMS

Vector DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.gbase.cn

www.h2database.com

github.com/heavyai/heavydb
www.heavy.ai

www.timescale.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

www.h2database.com/html/main.html

docs.heavy.ai

docs.timescale.com

Developer

General Data Technology Co., Ltd.

Thomas Mueller

HEAVY.AI, Inc.

Timescale

Initial release

2004

2005

2016

2017

2023

Current release

GBase 8a, GBase 8s, GBase 8c

2.2.220, July 2023

5.10, January 2022

2.15.0, May 2024

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

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

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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

C, Java, Python

Java

C++ and CUDA

C++

Server operating systems

Linux

All OS with a Java VM

Linux

Linux
OS X
Windows

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

Round robin

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication

Source-replica replication with hot standby and reads on replicas

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

yes

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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