DBMS > etcd vs. LevelDB vs. Microsoft Azure Cosmos DB vs. RisingWave vs. SAP IQ

System Properties Comparison etcd vs. LevelDB vs. Microsoft Azure Cosmos DB vs. RisingWave vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Globally distributed, horizontally scalable, multi-model database service

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Columnar RDBMS optimized for Big Data analytics

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

column-oriented

Secondary database models

Spatial DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

www.risingwave.com/database

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/azure/cosmos-db

docs.risingwave.com/docs/current/intro

help.sap.com/docs/SAP_IQ

Developer

Google

Microsoft

RisingWave Labs

SAP, formerly Sybase

Initial release

2011

2014

2022

1994

Current release

3.4, August 2019

1.23, February 2021

1.2, September 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

commercial

Open Source

Apache Version 2.0

commercial

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++

Rust

Server operating systems

FreeBSD
Linux
Windows

experimental

Illumos
Linux
OS X
Windows

hosted

Docker
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

Standard SQL-types and JSON

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
JSON over HTTP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

UDFs in Python or Java

yes

Triggers

yes, watching key changes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

none

yes

Implicit feature of the cloud service

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Access rights can be defined down to the item level

Users and Roles

fine grained access rights according to SQL-standard

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