DBMS > Alibaba Cloud TSDB vs. GeoMesa vs. Hive vs. RocksDB vs. Spark SQL

System Properties Comparison Alibaba Cloud TSDB vs. GeoMesa vs. Hive vs. RocksDB vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

www.geomesa.org/documentation/stable/user/index.html

cwiki.apache.org/confluence/display/Hive/Home

github.com/facebook/rocksdb/wiki

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

Developer

Alibaba

CCRi and others

Apache Software Foundation

initially developed by Facebook

Facebook, Inc.

Apache Software Foundation

Initial release

2014

2012

2013

2014

Current release

4.0.5, February 2024

3.1.3, April 2022

8.11.4, April 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache Version 2

Open Source

BSD

Open Source

Apache 2.0

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

Scala

Java

C++

Scala

Server operating systems

hosted

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

JDBC
ODBC
Thrift

C++ API
Java API

JDBC
ODBC

Supported programming languages

Java

C++
Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

Access managed on TSDB instance level

yes

depending on the DBMS used for storage

Access rights for users, groups and roles

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