DBMS > Ehcache vs. H2GIS vs. Kingbase vs. Pinecone vs. Sadas Engine

System Properties Comparison Ehcache vs. H2GIS vs. Kingbase vs. Pinecone vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Spatial extension of H2

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A managed, cloud-native vector database

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

Technical documentation

www.ehcache.org/documentation

www.h2gis.org/docs/home

docs.pinecone.io/docs/overview

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Terracotta Inc, owned by Software AG

CNRS

BeiJing KINGBASE Information technologies inc.

Pinecone Systems, Inc

SADAS s.r.l.

Initial release

2009

2013

1999

2019

2006

Current release

3.10.0, March 2022

V8.0, August 2021

8.0

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

LGPL 3.0

commercial

free trial version 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

Java

C and Java

C++

Server operating systems

All OS with a Java VM

Linux
Windows

hosted

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

APIs and other access methods

JCache

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

based on H2

user defined functions

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

based on H2

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

yes

based on H2

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

DZone Coding Java JBoss 5 to 7 in 11 steps
9 January 2014, dzone.com

provided by Google News

Made in China 2025 is back, with a new name and a focus on database companies – The China Project
19 December 2022, The China Project

Opening preparation - Alekhine defense, Saemisch variation
18 April 2016, Chess.com

Backup & Recovery Solutions from China
4 August 2022, Хабр

Distributed Database Market 2023 Trends with Analysis on Key Players Tencent, OceanBase, PingCAP
8 May 2024, Motions Online

provided by Google News

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone Launches Serverless Vector Database for Scalable AI Applications
21 May 2024, Datanami

Pinecone launches its serverless vector database out of preview
21 May 2024, Yahoo Lifestyle Australia

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

provided by Google News

Share this page