DBMS > EventStoreDB vs. LeanXcale vs. Oracle Rdb vs. Transwarp Hippo

System Properties Comparison EventStoreDB vs. LeanXcale vs. Oracle Rdb vs. Transwarp Hippo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Primary database model

Event Store

Key-value store
Relational DBMS

Relational DBMS

Vector DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

www.eventstore.com

www.leanxcale.com

www.oracle.com/database/technologies/related/rdb.html

www.transwarp.cn/en/subproduct/hippo

Technical documentation

developers.eventstore.com

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Event Store Limited

LeanXcale

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2012

2015

1984

2023

Current release

21.2, February 2021

7.4.1.1, 2021

1.0, May 2023

License

Commercial or Open Source

Open Source

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++

Server operating systems

Linux
Windows

HP Open VMS

Linux
macOS

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

C
Java
Scala

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes, on a single node

Concurrency

Support for concurrent manipulation of data

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

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

Oracle Adds New AI-Enabling Features To MySQL HeatWave
23 March 2023, Forbes

Should we all consolidate databases for the storage benefits? Reg vultures deploy DevOps, zoos, haircuts
18 September 2020, The Register

2013 Data Science Salary Survey – O'Reilly
4 May 2013, O'Reilly Media

provided by Google News

Share this page