DBMS > 4D vs. Blueflood vs. KeyDB vs. LevelDB vs. TimesTen

System Properties Comparison 4D vs. Blueflood vs. KeyDB vs. LevelDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Scalable TimeSeries DBMS based on Cassandra

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

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

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

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

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.4d.com

blueflood.io

github.com/Snapchat/KeyDB
keydb.dev

github.com/google/leveldb

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developer.4d.com

github.com/rax-maas/blueflood/wiki

docs.keydb.dev

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

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

Rackspace

EQ Alpha Technology Ltd.

Google

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1984

2013

2019

2011

1998

Current release

v20, April 2023

1.23, February 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

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

OS X
Windows

Linux
OS X

Linux

Illumos
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP REST

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Lua

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

with automatic compression on writes

yes

by means of logfiles and checkpoints

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 and groups

simple password-based access control and ACL

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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