DBMS > Blueflood vs. Google Cloud Spanner vs. LevelDB vs. Snowflake vs. Valentina Server

System Properties Comparison Blueflood vs. Google Cloud Spanner vs. LevelDB vs. Snowflake vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Object-relational database and reports server

Primary database model

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

blueflood.io

cloud.google.com/spanner

github.com/google/leveldb

www.snowflake.com

www.valentina-db.net

Technical documentation

github.com/rax-maas/blueflood/wiki

cloud.google.com/spanner/docs

github.com/google/leveldb/blob/main/doc/index.md

docs.snowflake.net/manuals/index.html

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

Developer

Rackspace

Google

Snowflake Computing Inc.

Paradigma Software

Initial release

2013

2017

2011

2014

1999

Current release

1.23, February 2021

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

commercial

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

Java

C++

Server operating systems

Linux
OS X

hosted

Illumos
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

predefined scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

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

Query statements complying to ANSI 2011

yes

APIs and other access methods

HTTP REST

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript (Node.js)
Python

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

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

Sharding

based on Cassandra

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication with 3 replicas for regional instances.

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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

fine grained access rights according to SQL-standard

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