DBMS > Snowflake vs. Transwarp Hippo vs. Valentina Server vs. XTDB

System Properties Comparison Snowflake vs. Transwarp Hippo vs. Valentina Server vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service for structured and semi-structured data

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

Object-relational database and reports server

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.snowflake.com

www.transwarp.cn/en/subproduct/hippo

www.valentina-db.net

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.snowflake.net/manuals/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

www.xtdb.com/docs

Developer

Snowflake Computing Inc.

Paradigma Software

Juxt Ltd.

Initial release

2014

2023

1999

2019

Current release

1.0, May 2023

5.7.5

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

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

C++

Clojure

Server operating systems

hosted

Linux
macOS

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

CLI Client
JDBC
ODBC

RESTful HTTP API

ODBC

HTTP REST
JDBC

Supported programming languages

JavaScript (Node.js)
Python

C++
Java
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, each node contains all data

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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