DBMS > BigObject vs. HarperDB vs. RethinkDB vs. Snowflake

System Properties Comparison BigObject vs. HarperDB vs. RethinkDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

docs.bigobject.io

docs.harperdb.io/docs

rethinkdb.com/docs

docs.snowflake.net/manuals/index.html

Developer

BigObject, Inc.

HarperDB

The Linux Foundation

since July 2017

Snowflake Computing Inc.

Initial release

2015

2017

2009

2014

Current release

3.1, August 2021

2.4.1, August 2020

License

Commercial or Open Source

commercial

free community edition available

commercial

free community edition available

Open Source

Apache 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

Node.js

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
OS X
Windows

hosted

Data scheme

yes

dynamic schema

schema-free

yes

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

Typing

predefined data types such as float or date

yes

JSON data types

yes

string, binary, float, bool, date, geometry

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

SQL-like DML and DDL statements

SQL-like data manipulation statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Custom Functions

since release 3.1

user defined functions

Triggers

Client-side triggers through changefeeds

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

range based

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

the nodes on which a table resides can be defined

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Atomic execution of specific operations

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

MVCC based

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 and roles

yes

users and table-level permissions

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

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