DBMS > Hive vs. Ignite vs. QuestDB vs. Redis vs. Stardog

System Properties Comparison Hive vs. Ignite vs. QuestDB vs. Redis vs. Stardog

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A high performance open source SQL database for time series data

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.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

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

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

questdb.io/docs

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

docs.stardog.com

Developer

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

QuestDB Technology Inc

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Stardog-Union

Initial release

2012

2015

2014

2009

2010

Current release

3.1.3, April 2022

Apache Ignite 2.6

7.2.5, May 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

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

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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.

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

Implementation language

Java

C++, Java, .Net

Java (Zero-GC), C++, Rust

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
macOS
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

schema-free

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

with RediSearch module

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

SQL with time-series extensions

with RediSQL module

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

proprietary protocol

RESP - REdis Serialization Protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes (compute grid and cache interceptors can be used instead)

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

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes (cache interceptors and events)

publish/subscribe channels provide some trigger functionality; RedisGears

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

Source-replica replication with eventual consistency

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

ACID for single-table writes

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

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

through memory mapped files

yes

User concepts

Access control

Access rights for users, groups and roles

Security Hooks for custom implementations

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

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
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Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
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Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
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Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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