DBMS > KeyDB vs. Microsoft Azure AI Search vs. RocksDB vs. Sqrrl vs. ToroDB

System Properties Comparison KeyDB vs. Microsoft Azure AI Search vs. RocksDB vs. Sqrrl vs. ToroDB

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Search-as-a-service for web and mobile app development

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Adaptable, secure NoSQL built on Apache Accumulo

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store

Search engine

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Vector DBMS

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

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

github.com/Snapchat/KeyDB
keydb.dev

azure.microsoft.com/en-us/services/search

rocksdb.org

sqrrl.com

github.com/torodb/server

Technical documentation

docs.keydb.dev

learn.microsoft.com/en-us/azure/search

github.com/facebook/rocksdb/wiki

Developer

EQ Alpha Technology Ltd.

Microsoft

Facebook, Inc.

Amazon

originally Sqrrl Data, Inc.

8Kdata

Initial release

2019

2015

2013

2012

2016

Current release

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSD-3

commercial

Open Source

BSD

commercial

Open Source

AGPL-V3

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.

Implementation language

C++

Java

Server operating systems

Linux

hosted

Linux

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

partial

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

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

RESTful HTTP API

C++ API
Java API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

C#
Java
JavaScript
Python

C
C++
Go
Java
Perl
Python
Ruby

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

selectable replication factor

making use of Hadoop

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

yes

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

simple password-based access control and ACL

yes

using Azure authentication

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

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