DBMS > Heroic vs. Lovefield vs. Tibero vs. Transwarp Hippo

System Properties Comparison Heroic vs. Lovefield vs. Tibero vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable relational database for web apps written in pure JavaScript

A secure RDBMS, designed for easy portability from Oracle

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

Primary database model

Time Series DBMS

Relational DBMS

Vector DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

github.com/spotify/heroic

google.github.io/lovefield

us.tmaxsoft.com/products/tibero

www.transwarp.cn/en/subproduct/hippo

Technical documentation

spotify.github.io/heroic

github.com/google/lovefield/blob/master/docs/spec_index.md

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Spotify

Google

TmaxSoft

Initial release

2014

2003

2023

Current release

2.1.12, February 2017

6, April 2015

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

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

Java

JavaScript

C and Assembler

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

RESTful HTTP API

Supported programming languages

JavaScript

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

C++
Java
Python

Server-side scripts

Stored procedures

Persistent Stored Procedure (PSM)

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

by range, hash, list or composite

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

planned for next version

yes

User concepts

Access control

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

Role based access control and fine grained access rights

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