DBMS > Drizzle vs. JSqlDb vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. NSDb

System Properties Comparison Drizzle vs. JSqlDb vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. NSDb

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.

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

JavaScript Query Language Database, stores JavaScript objects and primitives

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Key-value store

Relational DBMS

Time Series DBMS

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

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

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

jsqldb.org (offline)

github.com/Snapchat/KeyDB
keydb.dev

azure.microsoft.com/services/synapse-analytics

nsdb.io

Technical documentation

docs.keydb.dev

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

Developer

Drizzle project, originally started by Brian Aker

Konrad von Backstrom

EQ Alpha Technology Ltd.

Microsoft

Initial release

2008

2018

2019

2016

2017

Current release

7.2.4, September 2012

0.8, December 2018

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

BSD-3

commercial

Open Source

Apache Version 2.0

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

C++

Java, Scala

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Windows

Linux

hosted

Linux
macOS

Data scheme

yes

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

yes: int, bigint, decimal, string

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

by using the Redis Search module

yes

all fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C++
Java
PHP

JavaScript

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#
Java
PHP

Java
Scala

Server-side scripts

Stored procedures

functions in JavaScript

Lua

Transact SQL

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

using RocksDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

Using Apache Lucene

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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More resources

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