DBMS > Blueflood vs. Hazelcast vs. MaxDB vs. Percona Server for MongoDB vs. Snowflake

System Properties Comparison Blueflood vs. Hazelcast vs. MaxDB vs. Percona Server for MongoDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

A widely adopted in-memory data grid

A robust and reliable RDBMS optimized to run all major SAP solutions

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

blueflood.io

hazelcast.com

maxdb.sap.com

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

Technical documentation

github.com/rax-maas/blueflood/wiki

hazelcast.org/imdg/docs

maxdb.sap.com/documentation

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

Developer

Rackspace

Hazelcast

SAP, acquired from Software AG (Adabas-D) in 1997

Percona

Snowflake Computing Inc.

Initial release

2013

2008

1984

2015

2014

Current release

5.3.6, November 2023

7.9.10.12, February 2024

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

Limited community edition free

Open Source

GPL Version 2

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

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux

hosted

Data scheme

predefined scheme

schema-free

yes

schema-free

yes

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

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP REST

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C#
Java
Perl
PHP
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

JavaScript

user defined functions

Triggers

yes

Events

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Replicated Map

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

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

via In-Memory Engine

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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

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