DBMS > Drizzle vs. InfinityDB vs. KeyDB vs. SpaceTime vs. TerarkDB

System Properties Comparison Drizzle vs. InfinityDB vs. KeyDB vs. SpaceTime vs. TerarkDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Relational DBMS

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

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

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

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

boilerbay.com

github.com/Snapchat/KeyDB
keydb.dev

www.mireo.com/spacetime

github.com/bytedance/terarkdb

Technical documentation

boilerbay.com/infinitydb/manual

docs.keydb.dev

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Drizzle project, originally started by Brian Aker

Boiler Bay Inc.

EQ Alpha Technology Ltd.

Mireo

ByteDance, originally Terark

Initial release

2008

2002

2019

2020

2016

Current release

7.2.4, September 2012

4.0

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

BSD-3

commercial

restricted open source version available

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

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux

Data scheme

yes

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

schema-free

yes

schema-free

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.

Secondary indexes

yes

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

yes

by using the Redis Search module

SQL

Support of SQL

yes

with proprietary extensions

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC

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

Proprietary protocol

RESP - REdis Serialization Protoco

RESTful HTTP API

C++ API
Java API

Supported programming languages

C
C++
Java
PHP

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

C#
C++
Python

C++
Java

Server-side scripts

Stored procedures

Lua

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

Real-time block device replication (DRBD)

none

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

yes

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

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

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control and ACL

yes

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