DBMS > EsgynDB vs. Geode vs. RocksDB vs. Transwarp Hippo

System Properties Comparison EsgynDB vs. Geode vs. RocksDB vs. Transwarp Hippo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Relational DBMS

Key-value store

Vector DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Website

www.esgyn.cn

geode.apache.org

rocksdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

geode.apache.org/docs

github.com/facebook/rocksdb/wiki

Developer

Esgyn

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Facebook, Inc.

Initial release

2015

2002

2013

2023

Current release

1.1, February 2017

9.2.1, May 2024

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

BSD

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

Java

C++

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Linux
macOS

Data scheme

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

SQL

Support of SQL

yes

SQL-like query language (OQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

C++ API
Java API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

yes

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

fine grained access rights according to SQL-standard

Access rights per client and object definable

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.