DBMS > Apache Impala vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. Speedb

System Properties Comparison Apache Impala vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. Speedb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Document store

Spatial DBMS

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.26
Rank	#310	Overall
	#45	Key-value stores

Website

impala.apache.org

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

www.postgres-xl.org

www.speedb.io

Technical documentation

impala.apache.org/impala-docs.html

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

learn.microsoft.com/azure/cosmos-db

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

Microsoft

Speedb

Initial release

2013

2011

2014

since 2012, originally named StormDB

2020

Current release

4.1.0, June 2022

1.23, February 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD

commercial

Open Source

Mozilla public license

Open Source

Apache Version 2.0; commercial license available

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++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

hosted

Linux
macOS

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

XML type, but no XML query functionality

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

user defined functions

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

MVCC

yes

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 for users, groups and roles

based on Apache Sentry and Kerberos

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
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Competitive advantages

Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
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Licensing and pricing models

Open source - Speedb OSS is released under an Apache license and can be found on...
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