DBMS > BoltDB vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. OpenQM vs. Redis

System Properties Comparison BoltDB vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. OpenQM vs. Redis

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Fully managed big data interactive analytics platform

QpenQM is a high-performance, self-tuning, multi-value DBMS

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.

Primary database model

column oriented

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

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

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

Website

github.com/boltdb/bolt

www.elastic.co/elasticsearch

azure.microsoft.com/services/data-explorer

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

redis.com
redis.io

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

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

Developer

Elastic

Microsoft

Rocket Software, originally Martin Phillips

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2013

2010

2019

1993

2009

Current release

8.6, January 2023

cloud service with continuous releases

3.4-12

7.2.4, January 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Elastic License

commercial

Open Source

GPLv2, extended commercial license available

Open Source

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

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

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Fixed schema with schema-less datatypes (dynamic)

yes

with some exceptions

schema-free

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

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

All search fields are automatically indexed

all fields are automatically indexed

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

with RediSQL module

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
Basic
C
Java
Objective C
PHP
Python

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

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

yes

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

Triggers

yes

by using the 'percolation' feature

yes

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

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

yes

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate 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

yes

ACID

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

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Azure Active Directory Authentication

Access rights can be defined down to the item level

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

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