Apache AGE VS yugabyte-db

What about the AGE extension for Postgres? https://age.apache.org/

Waiting for Postgres to release theirs.

I think they are talking about the AGE extension https://age.apache.org

It's my understanding of the "incubation" period of Apache Software Foundation projects is to determine if they're able to actually execute the ASF process, and a bunch of other "project maturity metrics" (https://community.apache.org/apache-way/apache-project-matur...) of which AGE currently has some self-certification: https://age.apache.org/?l=maturity#

I recognize that's not exactly an answer to the question you asked, but I would be surprised if someone other than a project member knows a more forward-looking one

Postgres has a graph extension: https://age.apache.org. This means you can keep all your data in PG and use both models.

PostgreSQL with graph extension, developed by a team at Apache Software Foundation as Apache AGE. Apache AGE uses Gremlin.

The big thing that graph dbs provide is transitive traversals of join relationships.

The problem with graph dbs is trying to return something that is not a graph. Like a count. Or derived information. And which graph model do you use? There’s more than one. Lots of information is very poorly modeled in graph dbs. Temporal organization, for example.

Ultimately, graphs are a way to use relations. But relations allow you much more flexibility to associate information (subject to the issue of transitive relationship traversal).

Mixed graph-relational is perfectly reasonable. Reasonable start here: [https://age.apache.org/]

their actual landing page is actually better than the Github one. It's a translation layer(s) to allow querying Postgres using openCypher

Depending on how one views "postgres", there are at least two extensions that allegedly do it: https://age.apache.org/ and the AgensGraph from which AGE derives

There's an extension to postgresql (I haven't used it, but I am familiar with node/edge tables in MSSQL) that allows you to do this: https://age.apache.org/

YugabyteDB is a transactional database that brings together four must-have needs of cloud native apps – namely SQL as a flexible query language, low-latency performance, continuous availability, and globally-distributed scalability. Other databases do not serve all 4 of these needs simultaneously.

It is possible to apply Batched Nested Loop but with additional code that checks the range of the outer bigint and compare it only if it matches the range of integer. This has been added in YugabyteDB 2.21 with #20715 YSQL: Allow BNL on joins over different integer types to help migrations from PostgreSQL with such datatype inconsistencies.

It can be done like https://github.com/yugabyte/yugabyte-db/ has.

Therefore, interleaving or co-partitioning is probably not necessary, and would reduce agility and scalability more than improving the performance. Unless you have a good reason for it that you can share on Issue #79. But, first, test and tune the queries to see if you need something else.

This is a workaround, not supported. I've opened the following issue to get it solve in the YugabyteDB deployment: https://github.com/yugabyte/yugabyte-db/issues/19389

Note that there may still be a need for bitmaps, especially with disjunctions (OR) as the following is about conjunction (AND), and it can still be implemented, differently than PostgreSQL. This is tracked by #4634.

FROM almalinux:8 as build RUN dnf -y update &&\ dnf groupinstall -y 'Development Tools' # get YugabyteDB sources ARG YB_TAG=2.18 RUN git clone --branch ${YB_TAG} https://github.com/yugabyte/yugabyte-db.git WORKDIR yugabyte-db # install dependencies and compilation tools RUN dnf install -y https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm RUN dnf -y install epel-release libatomic rsync python3-devel cmake3 java-1.8.0-openjdk maven npm golang gcc-toolset-12 gcc-toolset-12-libatomic-devel patchelf glibc-langpack-en ccache vim wget python3.11-devel python3.11-pip clang ncurses-devel readline-devel libsqlite3x-devel RUN mkdir /opt/yb-build RUN chown "$USER" /opt/yb-build # Install Python 3 RUN alternatives --remove-all python3 RUN alternatives --remove-all python RUN alternatives --install /usr/bin/python python /usr/bin/python3.11 3 RUN alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 3 # add #include "pg_yb_utils.h" to src/postgres/src/pl/plpython/plpy_procedure.c RUN sed -e '/#include "postgres.h"/a#include "pg_yb_utils.h"' -i src/postgres/src/pl/plpython/plpy_procedure.c # if using python > 3.9 remove #include and #include from src/postgres/src/pl/plpython/plpython.h RUN sed -e '/#include /d' -e '/#include /d' -i src/postgres/src/pl/plpython/plpython.h # add '--with-python', to python/yugabyte/build_postgres.py under the configure_postgres method RUN sed -e "/'\.\/configure',/a\ '--with-python'," -i python/yugabyte/build_postgres.py # Build and package the release RUN YB_CCACHE_DIR="$HOME/.cache/yb_ccache" ./yb_build.sh -j$(nproc) --clean-all --build-yugabyted-ui --no-linuxbrew --clang15 -f release RUN chmod +x bin/get_clients.sh bin/parse_contention.py bin/yb-check-consistency.py RUN YB_USE_LINUXBREW=0 ./yb_release --force WORKDIR / RUN mv /yugabyte-db/build/yugabyte*.tar.gz /yugabyte.tgz

You have seen me using the official YugabyteDB Docker image extensively. This image is suitable for various purposes, including labs, development, testing, and even production. In the past, we used to create it internally due to its seamless integration with our build process. However, some companies prefer to construct the image on their own, which is indeed a commendable practice. After all, it's not advisable to run random images with root privileges on your servers. As a result, we have made a significant alteration by introducing a refined Dockerfile to our Github repository.

Of course, I can guess from the function names, but YugabyteDB is Open Source and I can search for them. What happens here is that I didn't declare a Primary Key for my table and then an internal one (ybctid) is generated, because secondary indexes need a key to address the table row. This ID generation calls /dev/urandom. I made this simple example to show that low-level traces can give a clue about high level data model problems.