DBMS > BigchainDB vs. InfinityDB vs. KeyDB vs. Memcached vs. Snowflake

System Properties Comparison BigchainDB vs. InfinityDB vs. KeyDB vs. Memcached vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

A Java embedded Key-Value Store which extends the Java Map interface

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

In-memory key-value store, originally intended for caching

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

Primary database model

Document store

Key-value store

Relational DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.bigchaindb.com

boilerbay.com

github.com/Snapchat/KeyDB
keydb.dev

www.memcached.org

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

boilerbay.com/infinitydb/manual

docs.keydb.dev

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

Developer

Boiler Bay Inc.

EQ Alpha Technology Ltd.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

Initial release

2016

2002

2019

2003

2014

Current release

4.0

1.6.27, May 2024

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

BSD-3

Open Source

BSD license

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

Python

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

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

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

manual creation possible, using inversions based on multi-value capability

yes

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

yes

simple password-based access control and ACL

yes

using SASL (Simple Authentication and Security Layer) protocol

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

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