DBMS > GeoSpock vs. RocksDB vs. SingleStore vs. TDengine

System Properties Comparison GeoSpock vs. RocksDB vs. SingleStore vs. TDengine

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Time Series DBMS and big data platform

Primary database model

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Relational DBMS

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

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

geospock.com

rocksdb.org

www.singlestore.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

github.com/facebook/rocksdb/wiki

docs.singlestore.com

docs.tdengine.com

Developer

GeoSpock

Facebook, Inc.

SingleStore Inc.

TDEngine, previously Taos Data

Initial release

2013

2019

Current release

2.0, September 2019

9.2.1, May 2024

8.5, January 2024

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

free developer edition available

Open Source

AGPL V3, also commercial editions 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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java, Javascript

C++

C++, Go

Server operating systems

hosted

Linux

64 bit version required

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

but no triggers and foreign keys

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

JDBC
RESTful HTTP API

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

Sharding

hash partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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 table

Fine grained access control via users, groups and roles

yes

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Mastering Memory Leak Detection in TDengine
31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.