DBMS > EJDB vs. Firebird vs. Greenplum vs. Redis vs. SingleStore

System Properties Comparison EJDB vs. Firebird vs. Greenplum vs. Redis vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Firebird is an open source RDBMS forked from Borland's InterBase

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

Primary database model

Document 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
Spatial DBMS

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

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

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

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

github.com/Softmotions/ejdb

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.firebirdsql.org/en/reference-manuals

docs.greenplum.org

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

docs.singlestore.com

Developer

Softmotions

Firebird Foundation

Pivotal Software Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SingleStore Inc.

Initial release

2012

2000

As fork of Borland's InterBase

2005

2009

2013

Current release

5.0.0, January 2024

7.0.0, September 2023

7.2.4, January 2024

8.5, January 2024

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

Open Source

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

commercial

free developer edition available

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C and C++

C++, Go

Server operating systems

server-less

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

64 bit version required

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

since Version 4.2

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

yes

with RediSQL module

yes

but no triggers and foreign keys

APIs and other access methods

in-process shared library

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC

proprietary protocol

RESP - REdis Serialization Protocol

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
Java
Perl
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

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

Server-side scripts

Stored procedures

PSQL

yes

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

yes

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

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

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

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

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

Read/Write Locking

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Data access is serialized by the server

yes, multi-version concurrency control (MVCC)

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.

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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

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