DBMS > GridDB vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. WakandaDB

System Properties Comparison GridDB vs. LevelDB vs. Microsoft Azure Synapse Analytics vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

griddb.net

github.com/google/leveldb

azure.microsoft.com/services/synapse-analytics

wakanda.github.io

Technical documentation

docs.griddb.net

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

docs.microsoft.com/azure/synapse-analytics

wakanda.github.io/doc

Developer

Toshiba Corporation

Google

Microsoft

Wakanda SAS

Initial release

2013

2011

2016

2012

Current release

5.1, August 2022

1.23, February 2021

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

BSD

commercial

Open Source

AGPLv3, extended 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++

C++, JavaScript

Server operating systems

Linux

Illumos
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
Java
PHP

JavaScript

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID at container level

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 for users can be defined per database

yes

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