tiedot is a document database engine that uses JSON as document
notation; it has a powerful query processor that supports advanced set
operations; it can be embedded into your program, or run a stand-alone
server using HTTP for an API.
tiedot has fault-tolerant data structures that put your data safety
first, while easily scales to 4+ CPU cores.
tiedot has very stable performance, even with millions of records! It
consistently achieves high throughput - swallow more than 120k records
or 80k complicated queries per second with confidence.
Release 12:
General performance improvements, including:
* Optimizations to space utilization and read/write performance for B-tree indexes
* Partitioning performance enhancements, including improved query performance on tables with thousands of partitions, improved insertion performance with INSERT and COPY, and the ability to execute ALTER TABLE ATTACH PARTITION without blocking queries
* Automatic (but overridable) inlining of common table expressions (CTEs)
* Reduction of WAL overhead for creation of GiST, GIN, and SP-GiST indexes
* Support for covering GiST indexes, via the INCLUDE clause
* Multi-column most-common-value (MCV) statistics can be defined via CREATE STATISTICS, to support better plans for queries that test several non-uniformly-distributed columns
Enhancements to administrative functionality, including:
* REINDEX CONCURRENTLY can rebuild an index without blocking writes to its table
* pg_checksums can enable/disable page checksums (used for detecting data corruption) in an offline cluster
* Progress reporting statistics for CREATE INDEX, REINDEX, CLUSTER, VACUUM FULL, and pg_checksums
Support for the SQL/JSON path language
Stored generated columns
Nondeterministic ICU collations, enabling case-insensitive and accent-insensitive grouping and ordering
New authentication features, including:
* Encryption of TCP/IP connections when using GSSAPI authentication
* Discovery of LDAP servers using DNS SRV records
* Multi-factor authentication, using the clientcert=verify-full option combined with an additional authentication method in pg_hba.conf
From David Weller-Fahy in PR pkg/54340.
DBF is a file format used by databases such dBase, Visual FoxPro, and
FoxBase+. This library reads DBF files and returns the data as native
Python data types for further processing. It is primarily intended for
batch jobs and one-off scripts.
ldb is a LDAP-like embedded database. It is not at all LDAP standards
compliant, so if you want a standards compliant database then please see the
excellent OpenLDAP project.
What ldb does is provide a fast database with an LDAP-like API designed to be
used within an application. In some ways it can be seen as a intermediate
solution between key-value pair databases and a real LDAP database.
ldb is the database engine used in Samba4.
Features:
* The main features that separate ldb from other solutions are:
* Safe multi-reader, multi-writer, using byte range locking
* LDAP-like API
* fast operation
* choice of local tdb or remote LDAP backends
* integration with talloc
* schema-less operation, for trivial setup
* modules for extensions (such as schema support)
* easy setup of indexes and attribute properties
* LDIF for import/export
* ldbedit tool for database (via LDIF) editing (reminiscent of 'vipw')
The Prometheus monitoring system and time series database.
Prometheus, a Cloud Native Computing Foundation project, is a systems and
service monitoring system. It collects metrics from configured targets at
given intervals, evaluates rule expressions, displays the results, and
can trigger alerts if some condition is observed to be true.
PostgreSQL 11 provides users with improvements to overall performance of the database system, with specific enhancements associated with very large databases and high computational workloads. Further, PostgreSQL 11 makes significant improvements to the table partitioning system, adds support for stored procedures capable of transaction management, improves query parallelism and adds parallelized data definition capabilities, and introduces just-in-time (JIT) compilation for accelerating the execution of expressions in queries.
Major enhancements in PostgreSQL 10 include:
Logical replication using publish/subscribe
Declarative table partitioning
Improved query parallelism
Significant general performance improvements
Stronger password authentication based on SCRAM-SHA-256
Improved monitoring and control
The above items are explained in more detail in the sections below.
