DBMS > Apache IoTDB vs. KeyDB vs. SQLite vs. Transwarp Hippo

System Properties Comparison Apache IoTDB vs. KeyDB vs. SQLite vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

Widely used embeddable, in-process RDBMS

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

iotdb.apache.org

github.com/Snapchat/KeyDB
keydb.dev

www.sqlite.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.keydb.dev

www.sqlite.org/docs.html

Developer

Apache Software Foundation

EQ Alpha Technology Ltd.

Dwayne Richard Hipp

Initial release

2018

2019

2000

2023

Current release

1.1.0, April 2023

3.46.1 (13 August 2024), August 2024

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD-3

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

server-less

Linux
macOS

Data scheme

yes

schema-free

yes

dynamic column types

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

not rigid because of 'dynamic typing' concept.

Vector, Numeric and String

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 query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
Native API

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

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

C++
Java
Python

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

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

In-memory capabilities

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

yes

User concepts

Access control

yes

simple password-based access control and ACL

Role based access control and fine grained access rights

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