DBMS > Ignite vs. LevelDB vs. Redis vs. Sadas Engine vs. Teradata Aster

System Properties Comparison Ignite vs. LevelDB vs. Redis vs. Sadas Engine vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Platform for big data analytics on multistructured data sources and types

Primary database model

Key-value store
Relational DBMS

Key-value store

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

Relational DBMS

Secondary database models

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

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

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

ignite.apache.org

github.com/google/leveldb

redis.com
redis.io

www.sadasengine.com

Technical documentation

apacheignite.readme.io/docs

github.com/google/leveldb/blob/main/doc/index.md

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

Google

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SADAS s.r.l.

Teradata

Initial release

2015

2011

2009

2006

2005

Current release

Apache Ignite 2.6

1.23, February 2021

7.2.5, May 2024

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

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

commercial

free trial version available

commercial

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

C++, Java, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

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

with RediSQL module

yes

APIs and other access methods

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

proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

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

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

R packages

Triggers

yes (cache interceptors and events)

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

through RedisGears

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

with automatic compression on writes

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

managed by 'Learn by Usage'

User concepts

Access control

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, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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