DBMS > Hazelcast vs. JSqlDb vs. Microsoft Azure Data Explorer vs. Redis vs. SiriDB

System Properties Comparison Hazelcast vs. JSqlDb vs. Microsoft Azure Data Explorer vs. Redis vs. SiriDB

Editorial information provided by DB-Engines

Name

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

Description

A widely adopted in-memory data grid

JavaScript Query Language Database, stores JavaScript objects and primitives

Fully managed big data interactive analytics platform

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Open Source Time Series DBMS

Primary database model

Key-value store

Document store
Object oriented DBMS

Relational DBMS

column oriented

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Time Series DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

hazelcast.com

jsqldb.org (offline)

azure.microsoft.com/services/data-explorer

redis.com
redis.io

siridb.com

Technical documentation

hazelcast.org/imdg/docs

docs.microsoft.com/en-us/azure/data-explorer

docs.redis.com/latest/index.html
redis.io/docs

docs.siridb.com

Developer

Hazelcast

Konrad von Backstrom

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Cesbit

Initial release

2008

2018

2019

2009

2017

Current release

5.3.6, November 2023

0.8, December 2018

cloud service with continuous releases

7.2.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

commercial

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Open Source

MIT License

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Java

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

hosted

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

partial

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

yes

Numeric data

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

all fields are automatically indexed

yes

with RediSearch module

yes

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

with RediSQL module

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

HTTP API

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

JavaScript

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

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++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

functions in JavaScript

Yes, possible languages: KQL, Python, R

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes

Events

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Spark connector (open source): github.com/Azure/azure-kusto-spark

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Role-based access control

Azure Active Directory Authentication

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

simple rights management via user accounts

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