DBMS > Ehcache vs. SWC-DB vs. Transwarp Hippo

System Properties Comparison Ehcache vs. SWC-DB vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A high performance, scalable Wide Column DBMS

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

Primary database model

Key-value store

Wide column store

Vector DBMS

Secondary database models

Time Series DBMS

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

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

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.ehcache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

www.ehcache.org/documentation

Developer

Terracotta Inc, owned by Software AG

Alex Kashirin

Initial release

2009

2020

2023

Current release

3.10.0, March 2022

0.5, April 2021

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux

Linux
macOS

Data scheme

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JCache

Proprietary protocol
Thrift

RESTful HTTP API

Supported programming languages

Java

C++

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

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

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Role based access control and fine grained access rights

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