DBMS > KeyDB vs. Spark SQL vs. SQLite vs. XTDB

System Properties Comparison KeyDB vs. Spark SQL vs. SQLite vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Relational DBMS

Document store

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

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/Snapchat/KeyDB
keydb.dev

spark.apache.org/sql

www.sqlite.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.keydb.dev

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

www.xtdb.com/docs

Developer

EQ Alpha Technology Ltd.

Apache Software Foundation

Dwayne Richard Hipp

Juxt Ltd.

Initial release

2019

2014

2000

2019

Current release

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD-3

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Scala

Clojure

Server operating systems

Linux

Linux
OS X
Windows

server-less

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

dynamic column types

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

not rigid because of 'dynamic typing' concept.

yes, extensible-data-notation format

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

limited SQL, making use of Apache Calcite

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP REST
JDBC

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

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java

Server-side scripts

Stored procedures

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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