DBMS > EXASOL vs. GeoSpock vs. Snowflake vs. SurrealDB vs. TerarkDB

System Properties Comparison EXASOL vs. GeoSpock vs. Snowflake vs. SurrealDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

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

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Spatial and temporal data processing engine for extreme data scale

Cloud-based data warehousing service for structured and semi-structured data

A fully ACID transactional, developer-friendly, multi-model DBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store
Graph DBMS

Key-value store

Secondary database models

Time Series DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.exasol.com

geospock.com

www.snowflake.com

surrealdb.com

github.com/bytedance/terarkdb

Technical documentation

www.exasol.com/resources

docs.snowflake.net/manuals/index.html

surrealdb.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Exasol

GeoSpock

Snowflake Computing Inc.

SurrealDB Ltd

ByteDance, originally Terark

Initial release

2000

2014

2022

2016

Current release

2.0, September 2019

v1.1.1, January 2024

License

Commercial or Open Source

commercial

Open Source

commercial

restricted open source version 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

Java, Javascript

Rust

C++

Server operating systems

hosted

Linux
macOS
Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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.

yes

Secondary indexes

yes

temporal, categorical

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

yes

SQL-like query language

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC

CLI Client
JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

C++ API
Java API

Supported programming languages

Java
Lua
Python
R

JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

C++
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights for users can be defined per table

Users with fine-grained authorization concept, user roles and pluggable authentication

yes, based on authentication and database rules

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