DBMS > jBASE vs. Redis vs. SingleStore vs. Tarantool

System Properties Comparison jBASE vs. Redis vs. SingleStore vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

A robust multi-value DBMS comprising development tools and middleware

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.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Multivalue DBMS

Key-value store

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

Relational DBMS

Document store
Key-value store
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

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.36
Rank	#157	Overall
	#3	Multivalue DBMS

Score	149.43
Rank	#6	Overall
	#1	Key-value stores

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Website

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

redis.com
redis.io

www.singlestore.com

www.tarantool.io

Technical documentation

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

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

docs.singlestore.com

www.tarantool.io/en/doc

Developer

Rocket Software (formerly Zumasys)

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SingleStore Inc.

Initial release

1991

2009

2013

2008

Current release

5.7

7.2.5, May 2024

8.5, January 2024

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

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

commercial

free developer edition available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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.

Implementation language

C++, Go

C and C++

Server operating systems

AIX
Linux
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

64 bit version required

BSD
Linux
macOS

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

optional

partial

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

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

with RediSearch module

yes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

with RediSQL module

yes

but no triggers and foreign keys

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

proprietary protocol

RESP - REdis Serialization Protocol

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Open binary protocol

Supported programming languages

.Net
Basic
Jabbascript
Java

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

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

yes

Lua, C and SQL stored procedures

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

hash partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes, multi-version concurrency control (MVCC)

yes, cooperative multitasking

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

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

Fine grained access control via users, groups and roles

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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