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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Amazon Timestream vs Symas LMDB

Amazon Timestream vs Symas LMDB

OverviewComparisonAlternatives

Overview

Symas LMDB
Symas LMDB
Stacks17
Followers36
Votes0
Amazon Timestream
Amazon Timestream
Stacks13
Followers50
Votes0

Amazon Timestream vs Symas LMDB: What are the differences?

What is Amazon Timestream? Fast, scalable, serverless time series database. It is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. It saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies.

What is Symas LMDB? *A memory-efficient database *. It is an extraordinarily fast, memory-efficient database which is developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases.

Amazon Timestream and Symas LMDB can be primarily classified as "Databases" tools.

Some of the features offered by Amazon Timestream are:

  • High performance at low cost
  • Serverless with auto-scaling
  • Data lifecycle management

On the other hand, Symas LMDB provides the following key features:

  • Ordered-map interface
  • Fully-transactional
  • Multi-thread and multi-process concurrency supported

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Detailed Comparison

Symas LMDB
Symas LMDB
Amazon Timestream
Amazon Timestream

It is an extraordinarily fast, memory-efficient database which is developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases.

It is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. It saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies.

Ordered-map interface; Fully-transactional; Multi-thread and multi-process concurrency supported
High performance at low cost; Serverless with auto-scaling; Data lifecycle management; Simplified data access; Purpose-built for time series; Always encrypted
Statistics
Stacks
17
Stacks
13
Followers
36
Followers
50
Votes
0
Votes
0
Integrations
Python
Python
Linux
Linux
Java
Java
Windows
Windows
macOS
macOS
Amazon Kinesis
Amazon Kinesis
Grafana
Grafana
Amazon SageMaker
Amazon SageMaker
Amazon Quicksight
Amazon Quicksight
Apache Flink
Apache Flink

What are some alternatives to Symas LMDB, Amazon Timestream?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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